KITS FOR DETECTING AND MONITORING ENDOCRINE DISRUPTING CHEMICALS (EDCs)

ABSTRACT

Described herein are compositions, a system, and kits for detection of endocrine disruptor chemicals (EDCs) in environmental samples, such as samples of water including but not limited to waste water treatment plant effluent, using a live-cell fluorescence-based nuclear translocation reporter system. Upon binding of a ligand to a fluorescent-labeled reporter protein, the protein (and therefore the fluorescence) is translocated in a ligand level-dependent manner from the cytoplasm to the nucleus of live mammalian cells; this translocation is detectable as diffuse (cytoplasmic) fluorescence converting to localized, brightly fluorescent nuclei. The described kits can be used to reliably detect very low levels of EDC contamination, including in high throughput analysis systems as described.

CROSS REFERENCE TO RELATED APPLICATION(S)

This application claims the benefit of the earlier filing date of U.S. provisional application No. 61/656,473, filed Jun. 6, 2012, and the entire content thereof is incorporated herein by reference in its entirety.

FIELD

This disclosure relates to methods, systems and kits for monitoring, detecting and/or measuring chemicals, such as endocrine disruptor chemicals, in environmental samples. This disclosure further relates to genetically engineered constructs that encode traceable fusion proteins that translocate from the cytoplasm to the nucleus in the presence of an endocrine disrupting chemical, and mammalian cells expressing one or more of such constructs.

BACKGROUND

An endocrine disruptor chemical (EDC) is an exogenous substance that impacts at least one function of an animal's endocrine system and consequently causes adverse health effects in an intact organism, its progeny, or (sub)populations. EDCs can cause adverse biological effects in animals and humans (Diamanti-Kandarakis et al., Horm. Metab Res 42:543-552, 2010).

Contamination of the environment, particularly water sources, with EDCs is a major concern for human health and threatens the integrity of aquatic ecosystems (Diamanti-Kandarakis et al., Endocr. Rev. 30:293-342, 2009; Deblonde et al., Int. J. Hyg. Environ. Health 214:442-448, 2011). Harmful effects of synthetic progestogens (Zeilinger et al., Environ. Toxicol. Chem. 28:2663-2670, 2009; Paulos et al., Aquat. Toxicol. 99:256-262, 2010) and especially of estrogenic water contaminants (Iwanowicz et al., Environ. Toxicol. Chem. 28:1072-1083, 2009; Alvarez et al., Environ. Toxicol. Chem. 28:1084-1095, 2009; Caldwell et al., Environ. Sci. Technol. 42:7046-7054, 2008; Lange et al., Environ. Toxicol. Chem. 20:1216-1227, 2001; Blazer et al., Environ. Monit. Assess. DOI 10.1007/s10661-0,1-2266-5, 2011) on fish reproduction are well documented. In addition, there is growing concern that environmental contamination with EDCs has deleterious effects on human reproduction, breast development and cancer, prostate cancer, neuroendocrinology, thyroid metabolism and obesity, and cardiovascular endocrinology (Diamanti-Kandarakis et al., Endocr. Rev. 30:293-342, 2009).

Glucocorticoids act through the glucocorticoid and mineralocorticoids receptors (GR and MR, respectively). Glucocorticoid deficiency is associated with a number of complex symptoms and is a life-threatening condition (Arlt & Allolio, Lancet 361:1881-1893, 2003). Naturally occurring glucocorticoids are released in mammalian organisms during the circadian cycle. However, excess exposure to glucocorticoids is associated with immune suppression and variety of other deleterious side effects (Schacke et al., Pharmacol. Ther. 96:23-43, 2002). Unoccupied glucocorticoid receptor resides in the cytoplasm and is bound to various heat-shock proteins and immunophilins in a large multi-protein complex (Pratt & Toft, Endocr. Rev. 18:306-360, 1997; Pratt et al., Handb. Exp. Pharmacol. 172:111-138, 2006). Upon hormone binding, GR dissociates from the chaperones and translocates to the cell nucleus, where it interacts with GR regulatory elements (GREs) and elicits GR-specific transcription regulation (John et al., Mol. Cell. 29:611-624, 2008).

At present, nothing is known about the prevalence of GCs activity in US water sources. However, using chemical methods, a few reports on water contamination in the Netherlands and China have demonstrated detectable levels of glucocorticoids (Schriks et al., Environ. Sci. Technol. 44:4766-4774, 2010; Change et al., Environ. Sci. Technol. 41:3462-3468, 2007). Another recent study has demonstrated that environmentally relevant concentrations of synthetic GCs have deleterious effects on fish (Kugathas & Sumpter, Environ. Sci. Technol. 45:2377-2383, 2011). The anti-inflammatory properties of the glucocorticoids make them highly prescribed pharmaceuticals. They could readily enter water sources and there are few sparse reports on water contamination with glucocorticoids (Schriks et al., Environ. Sci. Technol. 44:4766-4774, 2010; Chang et al., Environ. Sci. Technol. 41:3462-3468, 2007). Moreover, waste water treatment plants (WWTP) are not capable of efficiently removing glucocorticoids; it is well documented that anti-inflammatory chemicals are among the most resistant to treatment (30-40% of removal rate).

In spite of their importance, the levels of EDCs, such as steroidal EDCs, in the environment currently are not efficiently monitored and/or regulated. One of the reasons is that no high-throughput, reliable, low-cost detection methods exist for monitoring of biologically active EDCs. Current EDC detection relies on chemical analysis techniques (e.g., mass spectrometry, HPLC, GC, and other purely chemical analytical procedures), in vitro biologically-based but cell-free analysis techniques (e.g., purified receptor binding assays and immunoaffinity chromatography), in vitro cell-based analyses (e.g., cell proliferation assays and receptor-dependent gene expression assays, in human cells, or engineered yeast or bacterial cells), and in vivo analyses (e.g., uterotrophic and other growth/development assays in live rats or other animals). It is crucial to develop and implement novel high-throughput and low-cost methods for detection of EDCs in the environment. The need of such methods is well recognized in the field (Roy et al., J. Exp. Biol. 43:975-992, 2005). Existing methods for EDC detection may be sensitive, and in some instances are specific for individual ligands, but in general they are expensive, time-consuming, and largely incompatible with a large-scale sample testing.

SUMMARY

Described herein are methods, systems and kits for monitoring, detecting and/or measuring EDCs in environmental samples. These methods, systems and kits employ live mammalian (for instance, human) cells engineered to express at least one traceable fusion protein that changes its sub-cellular localization, for example translocates from the cytoplasm to the nucleus of the cell in the presence of an EDC. Specifically provided are cells and kits that detect more than one EDC, more than one class of EDC, and in some examples an array of EDCs simultaneously. Also provided are methods, systems and kits tailored for high throughput detection (and optionally quantification) of EDCs in environmental samples, such as water samples.

Provided herein in a first set of embodiments are systems for detecting or quantifying a ligand (e.g., an agonist or an antagonist) of a superfamily receptor protein in an environmental sample. In examples thereof, the system comprises a first mammalian cell expressing a first traceable fusion protein; a second mammalian cell expressing a second traceable fusion protein; and a detection system for the detection of the cytoplasm-to-nuclear translocation of the marker proteins, wherein the first and second traceable fusion proteins independently comprise either: (1) a superfamily receptor protein, and a marker protein domain; or (2) the cytoplasmic/nuclear translocation domain of glucocorticoid receptor, the ligand binding domain of a superfamily receptor protein, and a marker protein domain. Optionally, the mammalian cells are human cells.

Also described are systems for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample, wherein the ligand for the first or second traceable fusion protein is a natural ligand for the superfamily receptor protein of the traceable fusion protein, or a natural or synthetic compound that binds competitively therewith.

Also provided are systems for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample that additionally comprise one or more compounds and/or compositions that stably associate with a traceable fusion protein in the absence of a ligand for the ligand binding domain of the traceable fusion protein, and which dissociates from the fusion protein in the presence of a ligand for the ligand binding domain of the traceable fusion protein.

The systems described herein are optionally provided as kits.

Also described are methods for detecting or quantifying an endocrine disruptor chemical (EDC) ligand in an environmental sample, which methods involve contacting with the environmental sample a human cell expressing in its cytoplasm a fusion protein comprising: a receptor for the ligand, which receptor translocates from the cytoplasm to the nucleus upon ligand binding; and a marker protein domain; and then detecting cytoplasmic to nuclear translocation of the fusion protein in response to a ligand of the ligand binding domain in the water sample.

Additional described methods of determining the concentration of an endocrine disruptor chemical (EDC) ligand in an environmental sample involve contacting with the environmental sample a population of eukaryotic cells expressing in their cytoplasm a fusion protein comprising: a receptor for the ligand, which receptor translocates from the cytoplasm to the nucleus upon ligand binding; and a marker protein domain; and scanning one or more test cell(s) to obtain signal data from the marker of the fusion protein; converting the signal data to obtain the cellular location of the labeled protein in the test cell(s); and analyzing the signal data using an analysis system having an algorithm to calculate changes in distribution of the labeled fusion protein between the cytoplasm and the nucleus of the test cell(s), the analysis system having the capability of providing an accurate reading of the concentration of the ligand.

In any of the systems, kits, and methods described herein, the environmental sample can include a water sample, soil sample, or air sample. By way of example, where the environmental sample comprises a water sample, the sample includes in various embodiments one or more of surface water, sub-surface (ground) water, rain, run-off, well water, spring water, drinking water (processed or not), river water, estuary water, ocean water, effluent, treated sewage or untreated sewage.

The foregoing and other objects, features, and advantages of the invention will become more apparent from the following detailed description, which proceeds with reference to the accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

At least some of the figures submitted herewith are provided in full or part color.

FIG. 1A-E illustrates analysis of water samples for glucocorticoid and androgen contamination. FIG. 1A is a schematic representation of the GFP-tagged GR and AR receptor translocation in response to corresponding hormonal treatment. FIG. 1B is a series of micrographs showing GFP-GR translocation in a mammalian cell line (Walker et al., Methods (Comp. to Meth. Enzym.) 19:386-393, 1999) upon stimulation with dexamethasone for 30 minutes. Nuclei are stained with DAPI. Scale bar, 5 μm. FIG. 1C illustrates transcriptional activation of the GR-regulated Per1 gene by 10 water samples collected using a polar organic chemical integrative sampler (POCIS) are compared to transactivation induced by corticosterone. Data is normalized to DMSO alone. Blank and SS83 are POCIS negative controls. Error bars represent the mean±s.e.m., n=3. One of the water samples, SS97, induces complete GFP-GR translocation (image) and transcriptional activation of Per1 gene at a level higher than the activation induced by 100 nM corticosterone (graph). Scale bar, 5 μm. FIG. 1D is a GC/MS total ion chromatogram of HPLC fractionated sample SS97 (fraction 74-A), which revealed the presence of a complex mixture of volatile hydrocarbons, as indicated by the peaks. Database searching of the extracted MS spectra corresponding to peaks 1-3 showed structural similarity to known androstane-type steroids. GC/MS analysis of these peaks is presented in FIG. 3 and Table 3. FIG. 1E is a series of representative images of GFP-AR nuclear translocation in response to 100 nM of testosterone, androst-4-ene-3,6-dione, and sample SS97 (100×). Scale bar, 5 μm.

FIG. 2A-C illustrates collection sites of the first sample set and testing of HPLC fractions from sample SS97 for GR translocation. FIG. 2A illustrates the geographic locations of the collection sites of the first sample set collected by POCIS. One of the samples (marked with red, SS97) tested positive for GFP-GR translocation, suggesting a presence of glucocorticoid activity. Negative samples are marked with green. FIG. 2B shows GFP-GR translocation in a mammalian cell line (Walker et al., Methods (Comp. to Meth. Enzym.) 19:386-393, 1999) upon stimulation with 100 nM corticosterone for 30 min. Nuclei are stained with DAPI. Scale bar, 5 μm. FIG. 2C is a series of micrographs illustrating testing of HPLC fractions of sample SS97 (Fractions A-K) for GFP-GR translocation to determine the presence of glucocorticoid activity. Four of 11 fractions tested positive for GFP-GR translocation (FIG. 2C). Because GC/MS analyses detected atrazine in sample SS97, we included it in our analysis (bottom right). However, atrazine did not induce GFP-GR translocation.

FIG. 3 illustrates that database searching of the extracted MS chromatographic peaks 1-3 (FIG. 1D) suggests that the compounds were similar in structure to known androstane-type steroids. Visual comparison of the mass spectra of chromatographic peaks 1-3 (FIG. 1D) with standard spectra from the AES 2010 database suggests similarities to known androstane-class compounds.

FIG. 4A-E illustrates water sample screening by high throughput automated image analysis. FIG. 4A contains examples of images scored for cytoplasmic and nuclear segmentation from control and corticosterone treated 3617 cells. FIG. 4B is an illustration of a workflow for image-based screening of environmental contaminants with glucocorticoid activity using the Perkin Elmer Opera Image Screening System. FIG. 4C illustrates the automated image analysis output for a representative experiment. In this series, eight water samples from a total of 69 (well positions 2B, 2G, 3F, 4F, 9H, 10A, 10C, and 10E corresponding to samples R4E, R4A, R16W, R27, LF1a, 2a, 3a, and 4a (FIG. 4D) tested positive for GFP-GR translocation as indicated by color changes. Wells 1A-D represent four negative (DMSO) controls. Wells 1E-H are positive controls for cells treated with 100 nM corticosterone, and wells 10D, 10F and 10H are positive controls for cells treated with 100 nM dexamethasone. FIG. 4D and FIG. 4E are bar graphs illustrating quantitative analysis for GFP-GR and GFP-AR nuclear translocation, respectively. Translocation was calculated as a ratio of the nuclear versus cytoplasmic intensity, and each value was normalized to the control. Samples positive for glucocorticoid activity are marked with asterisks (P<0.01, red asterisks and P<0.05, black asterisks). Error bars represent the mean value±s.e.m, n=4.

FIG. 5A-C illustrates concentration-dependent translocation of GFP-GR and GFP-AR in response to their respective hormones as detected by the Opera (Perkin Elmer) automated imaging analysis system. FIG. 5A is a bar graph illustrating that GFP-GR translocates to the nucleus in a concentration-dependent manner upon treatment with known concentrations of hydrocortisone, dexamethasone, or corticosterone. An algorithm for cytoplasm and nuclear segmentation of the cells was used to determine the mean GFP-GR intensity in both compartments and translocation was quantified as a ratio of these intensities. Each value was normalized to the control sample. Error bars represent the mean value±s.e.m, n=6 (P<0.05, asterisks). FIG. 5B is a bar graph illustrating that GFP-AR translocation in response to known concentrations of testosterone. Insert shows that testosterone concentrations as low as 0.1 nM induced a statistically significant increase in the GFP-AR translocation. Samples with P<0.05 are indicated by an asterisk. Error bars represent the mean value±s.e.m, n=6. FIG. 5C is a bar graph illustrating that androst-4-en-3,6-dione induces concentration-dependent translocation of the GFP-AR construct (P<0.05, asterisks). Error bars represent the mean value±s.e.m, n=6.

FIG. 6A-B illustrates additional samples screened for GFP-GR nuclear translocation. FIG. 6A is an image analysis plate map showing a portion of GFP-GR expressing cells plated on a 384 well plate. Twenty two samples out of 38 (58%) tested positive for GFP-GR nuclear translocation. Wells 10A-H are negative controls (DMSO). Wells 1A-H and 9D, 9F, 9H are positive controls treated with 100 nM corticosterone and 100 nM dexamethasone, respectively. FIG. 6B is a bar graph GFP-GR nuclear translocation results summary. All samples in the gray box are POCIS negative controls. Positive samples are marked with asterisks (P<0.01, red asterisks and P<0.05, black asterisks). Error bars represent the mean value±s.e.m, n=4.

FIG. 7A-B illustrates additional samples screened for GFP-AR nuclear translocation. FIG. 7A is an image analysis plate map showing a portion of GFP-AR expressing cells plated on a 384 well plate. Twenty one samples out of 40 (55%) tested positive for GFP-AR nuclear translocation. Wells 10A-H are negative controls (DMSO). Wells 1A-H are positive controls for cells treated with 100 nM testosterone. FIG. 7B is a bar graph GFP-AR nuclear translocation results summary. All samples in the gray box are POCIS negative controls. Positive samples are marked with asterisks (P<0.01, red asterisks and P<0.05, black asterisks). Error bars represent the mean value±s.e.m, n=4.

FIG. 8 illustrates geographic locations of the collection sites and their contamination with glucocorticoid and androgenic activity. Negative samples are marked with green color. Samples positive for glucocorticoid activity are marked with black, androgen activity-positive samples are marked with pink, and samples positive for both activities are marked with red. Triangles indicate grab samples, while the circles indicate the use of POCIS membranes. For complete sample description (collection method as well as the time of collection and translocation activity) see Table 5A & 5B.

FIG. 9A-F illustrates concentration-dependent translocation and transcriptional activation induced by newly collected grab samples at location SS97. FIG. 9A and FIG. 9B are bar graphs illustrating concentration-dependent GFP-GRand GFP-AR translocation for sample SS97 four years after the initial collection. Translocation is calculated from the automatic image analysis and expressed as a ratio of nuclear versus cytoplasmic intensity normalized to DMSO treated control. Samples positive for glucocorticoid and androgen activities are marked with asterisks (P<0.05). Error bars represent the mean value±s.e.m, n=4. Significant increase in the GFP-GR translocation is detectable in 1× dilution for this sample (inset). While the lowest concentration inducing significant GFP-AR translocation was 10× (B, insert). FIG. 9C shows a representative heat-map for concentration-dependent GFP-GR translocation indicated as nuclear versus cytoplasmic intensity. Dex (dexamethasone, 100 nM), Cst (corticosterone, 100 nM), and HC (hydrocortisone, 100 nM) are included as positive controls as indicated on the bar graph above (FIG. 9A). FIG. 9D is a representative heat-map for the concentration-dependent GFP-AR translocation. Testosterone (Testo, 100 nM) was included as a positive control, as indicated on the bar graph above (FIG. 9B). FIG. 9E is a pair of bar graphs illustrating concentration-dependent transcriptional activation of the GR-regulated genes, Tgm2 and Lcn2. All tested concentrations (including lx) induced transcriptional responses of both genes, presented as fold change from the vehicle (DMSO) treated control. Dex (dexamethasone, 100 nM), Cst (corticosterone, 100 nM), and HC (hydrocortisone, 100 nM) are included as positive controls. Error bars represent the mean±s.e.m, n=4. FIG. 4F is a pair of bar graphs illustrating concentration-dependent transcriptional activation of the AR-regulated genes, NKX2.1 and RHOU by sample SS7 in LNCaP cells. Gene transcription was induced by the concentrations 10×, 20×, and 50× (P<0.05, asterisks), whereas higher concentrations seemed to have an inhibitory activity. Data is presented as fold change in comparison to the vehicle (DMSO) treated control. Androst-4-en-3,6-dione (A-4) (100 nM) and testosterone (Testo, 100 nM) were included as positive controls. Error bars represent the mean±s.e.m, n=4.

FIG. 10A-B illustrates concentration-dependent GFP-GR and GFP-AR translocation induced by the newly collected sample from the same location as SS97. FIG. 10A is a series of representative images for the concentration-dependent GFP-GR translocation in response to known concentrations of the water sample at site SS97. Scale bar, 10 μm. FIG. 10B is a series of representative images for concentration-dependent GFP-AR translocation in response to known concentrations of the water sample at site SS97. Scale bar, 10 μm.

FIG. 11A-B illustrates concentration-dependent GFP-GR and GFP-AR translocation induced by the newly collected sample from the same location as GL2W.

FIG. 11A is a series of representative images for concentration-dependent GFP-GR translocation in response to known concentrations of the water sample at site GL2W. Scale bar, 10 μm. FIG. 11B is a series of representative images for the concentration-dependent GFP-AR translocation in response to known concentrations of the water sample at site GL2W. Scale bar, 10 μm.

FIG. 12A-C illustrates concentration-dependent GFP-GR translocation and transcriptional activation of GR-regulated genes in response to the newly collected sample from the same location as GL2W. FIG. 12A is a bar graph illustrating translocation of GFP-GR in response to newly collected sample from the same location as GL2W (see also FIG. 11A). Translocation was calculated as a ratio of the nuclear versus cytoplasmic intensity and each value was further normalized to the value for the control sample. Samples positive for GFP-GR translocation are marked with asterisks (P<0.05). The lowest concentration inducing GFP-GR translocation is 10×. DMSO negative control, Dex (dexamethasone, 100 nM), Cst (corticosterone, 100 nM), and HC (hydrocortisone, 100 nM) were included as positive controls. Error bars represent the mean value±s.e.m, n=4. FIG. 12B is a representative raw data heat-map for GFP-GR translocation as in panel A. FIG. 12C is a series of bar graphs illustrating concentration-dependent transcriptional activation of three GR-regulated genes induced by newly collected sample from GL2W site. All concentrations induced transcriptional activation of at least one of the GR-regulated genes (P<0.05, asterisks). Transcription responses are presented as fold change in comparison to the vehicle control sample (DMSO). Dex (dexamethasone, 100 nM), Cst (corticosterone, 100 nM), and HC (hydrocortisone, 100 nM) are included as positive controls. Error bars represent the mean±s.e.m, n=4.

FIG. 13A-C illustrates concentration-dependent GFP-AR translocation and transcriptional activation of AR-regulated genes in response to the newly collected sample from GL2W site. FIG. 13A is a bar graph illustrating quantification of the GFP-AR concentration-dependent translocation response for the newly collected water sample at the GL2W site (see also FIG. 11B). Translocation was calculated as a ratio of the nuclear versus cytoplasmic intensity and each value was further normalized to the value for the control sample. Samples positive for GFP-AR translocation are marked with asterisks (P<0.05). The lowest sample concentration inducing GFP-AR translocation is 10×. Testosterone (Testo, 100 nM) is included as a positive control. Error bars represent the mean value±s.e.m, n=4. FIG. 13B is a representative raw data heat-map for GFP-AR translocation as in panel A. FIG. 13C is a pair of graphs illustrating concentration-dependent transcriptional activation of AR-regulated genes induced by newly collected sample from GL2W site in LNCaP cells which express endogenous AR. Concentrations 10× to 50× induced transcriptional activation in the AR-regulated genes NKX2.1 and RHOU (P<0.05, asterisks). At 100× concentration, we observed a reduced NKX2.1 expression, and did not detect change in RHOU transcription, suggesting the presence of an inhibitory activity (possibly anti-androgenic) which is apparent at that concentration. Transcriptional responses are presented as fold change in comparison to the vehicle treated (DMSO) control sample. Androst-4-en-3,6-dione (100 nM) and testosterone (Testo, 100 nM) are included as positive controls. Error bars represent the mean±s.e.m, n=4.

SEQUENCE LISTING

The nucleic and amino acid sequences listed in the accompanying sequence listing are shown using standard letter abbreviations for nucleotide bases, and three letter code for amino acids, as defined in 37 C.F.R. 1.822. Only one strand of each nucleic acid sequence is shown, but the complementary strand is understood as included by any reference to the displayed strand. The Sequence Listing is submitted as an ASCII text file named Sequences.txt, created on Jun. 6, 2013, ˜58 KB, which is incorporated by reference herein.

SEQ ID NO: 1 is the nucleic acid sequence which encodes traceable fusion protein pCI-nGFP-C656G. The sequence includes the following features at the indicated nucleotide positions:

6X His tag (8-24) HA Tag (28-59) GFP (60-780) GA Linker (781-810) Rat GR (829-3213), containing within it the C656G mutation (single point mutation T->G, codon changes from TGC->GGC) (2791; underlined) ATGGCCCACCATCACCACCATCACGGATATCCATACGACGTGCCAGATTACGCTCAGTCG AGTGCCATGAGTAAAGGAGAAGAACTTTTCACTGGAGTTGTCCCAATTCTTGTTGAATTA GATGGTGATGTTAATGGGCACAAATTTTCTGTCAGTGGAGAGGGTGAAGGTGATGCAACA TACGGAAAACTTACCCTTAAATTTATTTGCACTACTGGAAAACTACCTGTTCCTTGGCCA ACACTTGTCACTACTTTCACTTATGGTGTTCAATGCTTTTCAAGATACCCAGATCATATG AAACAGCATGACTTTTTCAAGAGTGCCATGCCCGAAGGTTATGTACAGGAAAGAACTATA TTTTTCAAAGATGACGGGAACTACAAGACACGTGCTGAAGTCAAGTTTGAAGGTGATACC CTTGTTAATAGAATCGAGTTAAAAGGTATTGATTTTAAAGAAGATGGAAACATTCTTGGA CACAAATTGGAATACAACTATAACTCACACAATGTATACATCATGGCAGACAAACAAAAG AATGGAATCAAAGTTAACTTCAAAATTAGACACAACATTGAAGATGGAAGCGTTCAACTA GCAGACCATTATCAACAAAATACTCCAATTGGCGATGGCCCTGTCCTTTTACCAGACAAC CATTACCTGTCCACACAATCTGCCCTTTCGAAAGATCCCAACGAAAAGAGAGACCACATG GTCCTTCTTGAGTTTGTAACAGCTGCTGGGATTACACATGGCATGGATGAACTATACAAA GGCGCCGGCGCTGGTGCTGGTGCTGGCGCCATCAGCGCGCTGATCCTGGACTCCAAAGAA TCCTTAGCTCCCCCTGGTAGAGACGAAGTCCCTGGCAGTTTGCTTGGCCAGGGGAGGGGG AGCGTAATGGACTTTTATAAAAGCCTGAGGGGAGGAGCTACAGTCAAGGTTTCTGCATCT TCGCCCTCAGTGGCTGCTGCTTCTCAGGCAGATTCCAAGCAGCAGAGGATTCTCCTTGAT TTCTCGAAAGGCTCCACAAGCAATGTGCAGCAGCGACAGCAGCAGCAGCAGCAGCAGCAG CAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCCAGGCTTATCCAAAGCCGTTTCACTG TCCATGGGGCTGTATATGGGAGAGACAGAAACAAAAGTGATGGGGAATGACTTGGGCTAC CCACAGCAGGGCCAACTTGGCCTTTCCTCTGGGGAAACAGACTTTCGGCTTCTGGAAGAA AGCATTGCAAACCTCAATAGGTCGACCAGCGTTCCAGAGAACCCCAAGAGTTCAACGTCT GCAACTGGGTGTGCTACCCCGACAGAGAAGGAGTTTCCCAAAACTCACTCGGATGCATCT TCAGAACAGCAAAATCGAAAAAGCCAGACCGGCACCAACGGAGGCAGTGTGAAATTGTAT CCCACAGACCAAAGCACCTTTGACCTCTTGAAGGATTTGGAGTTTTCCGCTGGGTCCCCA AGTAAAGACACAAACGAGAGTCCCTGGAGATCAGATCTGTTGATAGATGAAAACTTGCTT TCTCCTTTGGCGGGAGAAGATGATCCATTCCTTCTCGAAGGGAACACGAATGAGGATTGT AAGCCTCTTATTTTACCGGACACTAAACCTAAAATTAAGGATACTGGAGATACAATCTTA TCAAGTCCCAGCAGTGTGGCACTACCCCAAGTGAAAACAGAAAAAGATGATTTCATTGAA CTTTGCACCCCCGGGGTAATTAAGCAAGAGAAACTGGGCCCAGTTTATTGTCAGGCAAGC TTTTCTGGGACAAATATAATTGGTAATAAAATGTCTGCCATTTCTGTTCATGGTGTGAGT ACCTCTGGAGGACAGATGTACCACTATGACATGAATACAGCATCCCTTTCTCAGCAGCAG GATCAGAAGCCTGTTTTTAATGTCATTCCACCAATTCCTGTTGGTTCTGAAAACTGGAAT AGGTGCCAAGGCTCCGGAGAGGACAGCCTGACTTCCTTGGGGGCTCTGAACTTCCCAGGC CGGTCAGTGTTTTCTAATGGGTACTCAAGCCCTGGAATGAGACCAGATGTAAGCTCTCCT CCATCCAGCTCGTCAGCAGCCACGGGACCACCTCCCAAGCTCTGCCTGGTGTGCTCCGAT GAAGCTTCAGGATGTCATTACGGGGTGCTGACATGTGGAAGCTGCAAAGTATTCTTTAAA AGAGCAGTGGAAGGACAGCACAATTACCTTTGTGCTGGAAGAAACGATTGCATCATTGAT AAAATTCGAAGGAAAAACTGCCCAGCATGCCGCTATCGGAAATGTCTTCAGGCTGGAATG AACCTTGAAGCTCGAAAAACAAAGAAAAAAATCAAAGGGATTCAGCAAGCCACTGCAGGA GTCTCACAAGACACTTCGGAAAATCCTAACAAAACAATAGTTCCTGCAGCATTACCACAG CTCACCCCTACCTTGGTGTCACTGCTGGAGGTGATTGAACCCGAGGTGTTGTATGCAGGA TATGATAGCTCTGTTCCAGATTCAGCATGGAGAATTATGACCACACTCAACATGTTAGGT GGGCGTCAAGTGATTGCAGCAGTGAAATGGGCAAAGGCGATACTAGGCTTGAGAAACTTA CACCTCGATGACCAAATGACCCTGCTACAGTACTCATGGATGTTTCTCATGGCATTTGCC TTGGGTTGGAGATCATACAGACAATCAAGCGGAAACCTGCTCTGCTTTGCTCCTGATCTG ATTATTAATGAGCAGAGAATGTCTCTACCCGGCATGTATGACCAATGTAAACACATGCTG TTTGTCTCCTCTGAATTACAAAGATTGCAGGTATCCTATGAAGAGTATCTCTGTATGAAA ACCTTACTGCTTCTCTCCTCAGTTCCTAAGGAAGGTCTGAAGAGCCAAGAGTTATTTGAT GAGATTCGAATGACTTATATCAAAGAGCTAGGAAAAGCCATCGTCAAAAGGGAAGGGAAC TCCAGTCAGAACTGGCAACGGTTTTACCAACTGACAAAGCTTCTGGACTCCATGCATGAG GTGGTTGAGAATCTCCTTACCTACTGCTTCCAGACATTTTTGGATAAGACCATGAGTATT GAATTCCCAGAGATGTTAGCTGAAATCATCACTAATCAGATACCAAAATATTCAAATGGA AATATCAAAAAGCTTCTGTTTCATCAAAAATGA

SEQ ID NO: 2 is the amino acid sequence of traceable fusion protein pCI-nGFP-C656G. The sequence includes the following features at the indicated amino acid positions:

6X His tag (3-8) HA Tag (10-18) GFP (23-260) GA Linker (261-270) Rat GR (277-1070) C656G mutation (Cysteine to Glycine) (931; underlined) MAHHHHHHGYPYDVPDYAQSSAMSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDAT YGKLTLKFICTTGKLPVPWPTLVTTFTYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTI FFKDDGNYKTRAEVKFEGDTLVNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQK NGIKVNFKIRHNIEDGSVQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHM VLLEFVTAAGITHGMDELYKGAGAGAGAGAISALILDSKESLAPPGRDEVPGSLLGQGRG SVMDFYKSLRGGATVKVSASSPSVAAASQADSKQQRILLDFSKGSTSNVQQRQQQQQQQQ QQQQQQQQQQQPGLSKAVSLSMGLYMGETETKVMGNDLGYPQQGQLGLSSGETDFRLLEE SIANLNRSTSVPENPKSSTSATGCATPTEKEFPKTHSDASSEQQNRKSQTGTNGGSVKLY PTDQSTFDLLKDLEFSAGSPSKDTNESPWRSDLLIDENLLSPLAGEDDPFLLEGNTNEDC KPLILPDTKPKIKDTGDTILSSPSSVALPQVKTEKDDFIELCTPGVIKQEKLGPVYCQAS FSGTNIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPVFNVIPPIPVGSENWN RCQGSGEDSLTSLGALNFPGRSVFSNGYSSPGMRPDVSSPPSSSSAATGPPPKLCLVCSD EASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKNCPACRYRKCLQAGM NLEARKTKKKIKGIQQATAGVSQDTSENPNKTIVPAALPQLTPTLVSLLEVIEPEVLYAG YDSSVPDSAWRIMTTLNMLGGRQVIAAVKWAKAILGLRNLHLDDQMTLLQYSWMFLMAFA LGWRSYRQSSGNLLCFAPDLIINEQRMSLPGMYDQCKHMLFVSSELQRLQVSYEEYLCMK TLLLLSSVPKEGLKSQELFDEIRMTYIKELGKAIVKREGNSSQNWQRFYQLTKLLDSMHE VVENLLTYCFQTFLDKTMSIEFPEMLAEIITNQIPKYSNGNIKKLLFHQK*

SEQ ID NO: 3 is the nucleic acid sequence which encodes traceable fusion protein eGFP-hAR. The sequence includes the following features at the indicated nucleotide positions:

EGFP (1-717) Vector polylinker (718-752 hAR (753-3516) ATGGTGAGCAAGGGCGAGGAGCTGTTCACCGGGGTGGTGCCCATCCTGGTCGAGCTGGAC GGCGACGTAAACGGCCACAAGTTCAGCGTGTCCGGCGAGGGCGAGGGCGATGCCACCTAC GGCAAGCTGACCCTGAAGTTCATCTGCACCACCGGCAAGCTGCCCGTGCCCTGGCCCACC CTCGTGACCACCCTGACCTACGGCGTGCAGTGCTTCAGCCGCTACCCCGACCACATGAAG CAGCACGACTTCTTCAAGTCCGCCATGCCCGAAGGCTACGTCCAGGAGCGCACCATCTTC TTCAAGGACGACGGCAACTACAAGACCCGCGCCGAGGTGAAGTTCGAGGGCGACACCCTG GTGAACCGCATCGAGCTGAAGGGCATCGACTTCAAGGAGGACGGCAACATCCTGGGGCAC AAGCTGGAGTACAACTACAACAGCCACAACGTCTATATCATGGCCGACAAGCAGAAGAAC GGCATCAAGGTGAACTTCAAGATCCGCCACAACATCGAGGACGGCAGCGTGCAGCTCGCC GACCACTACCAGCAGAACACCCCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCAC TACCTGAGCACCCAGTCCGCCCTGAGCAAAGACCCCAACGAGAAGCGCGATCACATGGTC CTGCTGGAGTTCGTGACCGCCGCCGGGATCACTCTCGGCATGGACGAGCTGTACAAGTCC GGACTCAGATCTCGAGCTCAAGCTTCGAATTCGATGGAAGTGCAGTTAGGGCTGGGAAGG GTCTACCCTCGGCCGCCGTCCAAGACCTACCGAGGAGCTTTCCAGAATCTGTTCCAGAGC GTGCGCGAAGTGATCCAGAACCCGGGCCCCAGGCACCCAGAGGCCGCGAGCGCAGCACCT CCCGGCGCCAGTTTGCTGCTGCTGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAG CAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAAGAGACTAGCCCCAGGCAGCAGCAGCAG CAGCAGGGTGAGGATGGTTCTCCCCAAGCCCATCGTAGAGGCCCCACAGGCTACCTGGTC CTGGATGAGGAACAGCAACCTTCACAGCCGCAGTCGGCCCTGGAGTGCCACCCCGAGAGA GGTTGCGTCCCAGAGCCTGGAGCCGCCGTGGCCGCCAGCAAGGGGCTGCCGCAGCAGCTG CCAGCACCTCCGGACGAGGATGACTCAGCTGCCCCATCCACGTTGTCCCTGCTGGGCCCC ACTTTCCCCGGCTTAAGCAGCTGCTCCGCTGACCTTAAAGACATCCTGAGCGAGGCCAGC ACCATGCAACTCCTTCAGCAACAGCAGCAGGAAGCAGTATCCGAAGGCAGCAGCAGCGGG AGAGCGAGGGAGGCCTCGGGGGCTCCCACTTCCTCCAAGGACAATTACTTAGGGGGCACT TCGACCATTTCTGACAACGCCAAGGAGTTGTGTAAGGCAGTGTCGGTGTCCATGGGCCTG GGTGTGGAGGCGTTGGAGCATCTGAGTCCAGGGGAACAGCTTCGGGGGGATTGCATGTAC GCCCCACTTTTGGGAGTTCCACCCGCTGTGCGTCCCACTCCTTGTGCCCCATTGGCCGAA TGCAAAGGTTCTCTGCTAGACGACAGCGCAGGCAAGAGCACTGAAGATACTGCTGAGTAT TCCCCTTTCAAGGGAGGTTACACCAAAGGGCTAGAAGGCGAGAGCCTAGGCTGCTCTGGC AGCGCTGCAGCAGGGAGCTCCGGGACACTTGAACTGCCGTCTACCCTGTCTCTCTACAAG TCCGGAGCACTGGACGAGGCAGCTGCGTACCAGAGTCGCGACTACTACAACTTTCCACTG GCTCTGGCCGGACCGCCGCCCCCTCCGCCGCCTCCCCATCCCCACGCTCGCATCAAGCTG GAGAACCCGCTGGACTACGGCAGCGCCTGGGCGGCTGCGGCGGCGCAGTGCCGCTATGGG GACCTGGCGAGCCTGCATGGCGCGGGTGCAGCGGGACCCGGTTCTGGGTCACCCTCAGCC GCCGCTTCCTCATCCTGGCACACTCTCTTCACAGCCGAAGAAGGCCAGTTGTATGGACCG TGTGGTGGTGGTGGGGGTGGTGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGC GGCGGCGGCGGCGAGGCGGGAGCTGTAGCCCCCTACGGCTACACTCGGCCCCCTCAGGGG CTGGCGGGCCAGGAAAGCGACTTCACCGCACCTGATGTGTGGTACCCTGGCGGCATGGTG AGCAGAGTGCCCTATCCCAGTCCCACTTGTGTCAAAAGCGAAATGGGCCCCTGGATGGAT AGCTACTCCGGACCTTACGGGGACATGCGTTTGGAGACTGCCAGGGACCATGTTTTGCCC ATTGACTATTACTTTCCACCCCAGAAGACCTGCCTGATCTGTGGAGATGAAGCTTCTGGG TGTCACTATGGAGCTCTCACATGTGGAAGCTGCAAGGTCTTCTTCAAAAGAGCCGCTGAA GGGAAACAGAAGTACCTGTGCGCCAGCAGAAATGATTGCACTATTGATAAATTCCGAAGG AAAAATTGTCCATCTTGTCGTCTTCGGAAATGTTATGAAGCAGGGATGACTCTGGGAGCC CGGAAGCTGAAGAAACTTGGTAATCTGAAACTACAGGAGGAAGGAGAGGCTTCCAGCACC ACCAGCCCCACTGAGGAGACAACCCAGAAGCTGACAGTGTCACACATTGAAGGCTATGAA TGTCAGCCCATCTTTCTGAATGTCCTGGAAGCCATTGAGCCAGGTGTAGTGTGTGCTGGA CACGACAACAACCAGCCCGACTCCTTTGCAGCCTTGCTCTCTAGCCTCAATGAACTGGGA GAGAGACAGCTTGTACACGTGGTCAAGTGGGCCAAGGCCTTGCCTGGCTTCCGCAACTTA CACGTGGACGACCAGATGGCTGTCATTCAGTACTCCTGGATGGGGCTCATGGTGTTTGCC ATGGGCTGGCGATCCTTCACCAATGTCAACTCCAGGATGCTCTACTTCGCCCCTGATCTG GTTTTCAATGAGTACCGCATGCACAAGTCCCGGATGTACAGCCAGTGTGTCCGAATGAGG CACCTCTCTCAAGAGTTTGGATGGCTCCAAATCACCCCCCAGGAATTCCTGTGCATGAAA GCACTGCTACTCTTCAGCATTATTCCAGTGGATGGGCTGAAAAATCAAAAATTCTTTGAT GAACTTCGAATGAACTACATCAAGGAACTCGATCGTATCATTGCATGCAAAAGAAAAAAT CCCACATCCTGCTCAAGACGCTTCTACCAGCTCACCAAGCTCCTGGACTCCGTGCAGCCT ATTGCGAGAGAGCTGCATCAGTTCACTTTTGACCTGCTAATCAAGTCACACATGGTGAGC GTGGACTTTCCGGAAATGATGGCAGAGATCATCTCTGTGCAAGTGCCCAAGATCCTTTCT GGGAAAGTCAAGCCCATCTATTTCCACACCCAGTGA

SEQ ID NO: 4 is the amino acid sequence of traceable fusion protein eGFP-hAR. The sequence includes the following features at the indicated amino acid positions:

EGFP (1-239) Vector polylinker (240-251) hAR (252-1171) MVSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPT LVTTLTYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTL VNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLA DHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITLGMDELYKS GLRSRAQASNSMEVQLGLGRVYPRPPSKTYRGAFQNLFQSVREVIQNPGPRHPEAASAAP PGASLLLLQQQQQQQQQQQQQQQQQQQQQQQETSPRQQQQQQGEDGSPQAHRRGPTGYLV LDEEQQPSQPQSALECHPERGCVPEPGAAVAASKGLPQQLPAPPDEDDSAAPSTLSLLGP TFPGLSSCSADLKDILSEASTMQLLQQQQQEAVSEGSSSGRAREASGAPTSSKDNYLGGT STISDNAKELCKAVSVSMGLGVEALEHLSPGEQLRGDCMYAPLLGVPPAVRPTPCAPLAE CKGSLLDDSAGKSTEDTAEYSPFKGGYTKGLEGESLGCSGSAAAGSSGTLELPSTLSLYK SGALDEAAAYQSRDYYNFPLALAGPPPPPPPPHPHARIKLENPLDYGSAWAAAAAQCRYG DLASLHGAGAAGPGSGSPSAAASSSWHTLFTAEEGQLYGPCGGGGGGGGGGGGGGGGGGG GGGGEAGAVAPYGYTRPPQGLAGQESDFTAPDVWYPGGMVSRVPYPSPTCVKSEMGPWMD SYSGPYGDMRLETARDHVLPIDYYFPPQKTCLICGDEASGCHYGALTCGSCKVFFKRAAE GKQKYLCASRNDCTIDKFRRKNCPSCRLRKCYEAGMTLGARKLKKLGNLKLQEEGEASST TSPTEETTQKLTVSHIEGYECQPIFLNVLEAIEPGVVCAGHDNNQPDSFAALLSSLNELG ERQLVHVVKWAKALPGFRNLHVDDQMAVIQYSWMGLMVFAMGWRSFTNVNSRMLYFAPDL VFNEYRMHKSRMYSQCVRMRHLSQEFGWLQITPQEFLCMKALLLFSIIPVDGLKNQKFFD ELRMNYIKELDRIIACKRKNPTSCSRRFYQLTKLLDSVQPIARELHQFTFDLLIKSHMVS VDFPEMMAEIISVQVPKILSGKVKPIYFHTQ*

SEQ ID NO: 5 is the nucleic acid sequence which encodes traceable fusion protein eGFP-GR-ER310. The sequence includes the following features at the indicated nucleotide positions:

EGFP (1-717) GA Linker (718-747) hGR (748-2400) hER (2401-3261) ATGGTGAGCAAGGGCGAGGAGCTGTTCACCGGGGTGGTGCCCATCCTGGTCGAGCTGGAC GGCGACGTAAACGGCCACAAGTTCAGCGTGTCCGGCGAGGGCGAGGGCGATGCCACCTAC GGCAAGCTGACCCTGAAGTTCATCTGCACCACCGGCAAGCTGCCCGTGCCCTGGCCCACC CTCGTGACCACCCTGACCTACGGCGTGCAGTGCTTCAGCCGCTACCCCGACCACATGAAG CAGCACGACTTCTTCAAGTCCGCCATGCCCGAAGGCTACGTCCAGGAGCGCACCATCTTC TTCAAGGACGACGGCAACTACAAGACCCGCGCCGAGGTGAAGTTCGAGGGCGACACCCTG GTGAACCGCATCGAGCTGAAGGGCATCGACTTCAAGGAGGACGGCAACATCCTGGGGCAC AAGCTGGAGTACAACTACAACAGCCACAACGTCTATATCATGGCCGACAAGCAGAAGAAC GGCATCAAGGTGAACTTCAAGATCCGCCACAACATCGAGGACGGCAGCGTGCAGCTCGCC GACCACTACCAGCAGAACACCCCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCAC TACCTGAGCACCCAGTCCGCCCTGAGCAAAGACCCCAACGAGAAGCGCGATCACATGGTC CTGCTGGAGTTCGTGACCGCCGCCGGGATCACTCTCGGCATGGACGAGCTGTACAAGGGC GCTGGAGCAGGGGCTGGAGCCGGAGCTGACTCCAAAGAATCATTAACTCCTGGTAGAGAA GAAAACCCCAGCAGTGTGCTTGCTCAGGAGAGGGGAGATGTGATGGACTTCTATAAAACC CTAAGAGGAGGAGCTACTGTGAAGGTTTCTGCGTCTTCACCCTCACTGGCTGTCGCTTCT CAATCAGACTCCAAGCAGCGAAGACTTTTGGTTGATTTTCCAAAAGGCTCAGTAAGCAAT GCGCAGCAGCCAGATCTGTCCAAAGCAGTTTCACTCTCAATGGGACTGTATATGGGAGAG ACAGAAACAAAAGTGATGGGAAATGACCTGGGATTCCCACAGCAGGGCCAAATCAGCCTT TCCTCGGGGGAAACAGACTTAAAGCTTTTGGAAGAAAGCATTGCAAACCTCAATAGGTCG ACCAGTGTTCCAGAGAACCCCAAGAGTTCAGCATCCACTGCTGTGTCTGCTGCCCCCACA GAGAAGGAGTTTCCAAAAACTCACTCTGATGTATCTTCAGAACAGCAACATTTGAAGGGC CAGACTGGCACCAACGGTGGCAATGTGAAATTGTATACCACAGACCAAAGCACCTTTGAC ATTTTGCAGGATTTGGAGTTTTCTTCTGGGTCCCCAGGTAAAGAGACGAATGAGAGTCCT TGGAGATCAGACCTGTTGATAGATGAAAACTGTTTGCTTTCTCCTCTGGCGGGAGAAGAC GATTCATTCCTTTTGGAAGGAAACTCGAATGAGGACTGCAAGCCTCTCATTTTACCGGAC ACTAAACCCAAAATTAAGGATAATGGAGATCTGGTTTTGTCAAGCCCCAGTAATGTAACA CTGCCCCAAGTGAAAACAGAAAAAGAAGATTTCATCGAACTCTGCACCCCTGGGGTAATT AAGCAAGAGAAACTGGGCACAGTTTACTGTCAGGCAAGCTTTCCTGGAGCAAATATAATT GGTAATAAAATGTCTGCCATTTCTGTTCATGGTGTGAGTACCTCTGGAGGACAGATGTAC CACTATGACATGAATACAGCATCCCTTTCTCAACAGCAGGATCAGAAGCCTATTTTTAAT GTCATTCCACCAATTCCCGTTGGTTCCGAAAATTGGAATAGGTGCCAAGGATCTGGAGAT GACAACTTGACTTCTCTGGGGACTCTGAACTTCCCTGGTCGAACAGTTTTTTCTAATGGC TATTCAAGCCCCAGCATGAGACCAGATGTAAGCTCTCCTCCATCCAGCTCCTCAACAGCA ACAACAGGACCACCTCCCAAACTCTGCCTGGTGTGCTCTGATGAAGCTTCAGGATGTCAT TATGGAGTCTTAACTTGTGGAAGCTGTAAAGTTTTCTTCAAAAGAGCAGTGGAAGGACAG CACAATTACCTATGTGCTGGAAGGAATGATTGCATCATCGATAAAATTCGAAGAAAAAAC TGCCCAGCATGCCGCTATCGAAAATGTCTTCAGGCTGGAATGAACCTGGAAGCTCGAAAA ACAAAGAAAAAAATAAAAGGAATTCAGCAGGCCACTACAGGAGTCTCACAAGAAACCTCT GAAAATCCTGGTAACAAAACAATAGTTCCTGCAACGTTACCACAACTCACCCCTACCCTG GTGTCACTGTTGGAGGTTATTGAACCTGAAGTGTTATATGCAGGATATGATAGCTCTGTT CTGACGGCCGACCAGATGGTCAGTGCCTTGTTGGATGCTGAGCCCCCCATACTCTATTCC GAGTATGATCCTACCAGACCCTTCAGTGAAGCTTCGATGATGGGCTTACTGACCAACCTG GCAGACAGGGAGCTGGTTCACATGATCAACTGGGCGAAGAGGGTGCCAGGCTTTGTGGAT TTGACCCTCCATGATCAGGTCCACCTTCTAGAATGTGCCTGGCTAGAGATCCTGATGATT GGTCTCGTCTGGCGCTCCATGGAGCACCCAGGGAAGCTACTGTTTGCTCCTAACTTGCTC TTGGACAGGAACCAGGGAAAATGTGTAGAGGGCATGGTGGAGATCTTCGACATGCTGCTG GCTACATCATCTCGGTTCCGCATGATGAATCTGCAGGGAGAGGAGTTTGTGTGCCTCAAA TCTATTATTTTGCTTAATTCTGGAGTGTACACATTTCTGTCCAGCACCCTGAAGTCTCTG GAAGAGAAGGACCATATCCACCGAGTCCTGGACAAGATCACAGACACTTTGATCCACCTG ATGGCCAAGGCAGGCCTGACCCTGCAGCAGCAGCACCAGCGGCTGGCCCAGCTCCTCCTC ATCCTCTCCCACATCAGGCACATGAGTAACAAAGGCATGGAGCATCTGTACAGCATGAAG TGCAAGAACGTGGTGCCCCTCTATGACCTGCTGCTGGAGATGCTGGACGCCCACCGCCTA CATGCGCCCACTAGCCGTGGAGGGGCATCCGTGGAGGAGACGGACCAAAGCCACTTGGCC ACTGCGGGCTCTACTTCATCGCATTCCTTGCAAAAGTATTACATCACGGGGGAGGCAGAG GGTTTCCCTGCCACGGTCTAA

SEQ ID NO: 6 is the amino acid sequence of traceable fusion protein eGFP-GR-ER310. The sequence includes the following features at the indicated amino acid positions:

EGFP (1-239) GA Linker (240-249) hGR (250-800) hER (801-1086) MVSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPT LVTTLTYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTL VNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLA DHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITLGMDELYKG AGAGAGAGADSKESLTPGREENPSSVLAQERGDVMDFYKTLRGGATVKVSASSPSLAVAS QSDSKQRRLLVDFPKGSVSNAQQPDLSKAVSLSMGLYMGETETKVMGNDLGFPQQGQISL SSGETDLKLLEESIANLNRSTSVPENPKSSASTAVSAAPTEKEFPKTHSDVSSEQQHLKG QTGTNGGNVKLYTTDQSTFDILQDLEFSSGSPGKETNESPWRSDLLIDENCLLSPLAGED DSFLLEGNSNEDCKPLILPDTKPKIKDNGDLVLSSPSNVTLPQVKTEKEDFIELCTPGVI KQEKLGTVYCQASFPGANIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPIFN VIPPIPVGSENWNRCQGSGDDNLTSLGTLNFPGRTVFSNGYSSPSMRPDVSSPPSSSSTA TTGPPPKLCLVCSDEASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKN CPACRYRKCLQAGMNLEARKTKKKIKGIQQATTGVSQETSENPGNKTIVPATLPQLTPTL VSLLEVIEPEVLYAGYDSSVLTADQMVSALLDAEPPILYSEYDPTRPFSEASMMGLLTNL ADRELVHMINWAKRVPGFVDLTLHDQVHLLECAWLEILMIGLVWRSMEHPGKLLFAPNLL LDRNQGKCVEGMVEIFDMLLATSSRFRMMNLQGEEFVCLKSIILLNSGVYTFLSSTLKSL EEKDHIHRVLDKITDTLIHLMAKAGLTLQQQHQRLAQLLLILSHIRHMSNKGMEHLYSMK CKNVVPLYDLLLEMLDAHRLHAPTSRGGASVEETDQSHLATAGSTSSHSLQKYYITGEAE GFPATV*

SEQ ID NO: 7 is the nucleic acid sequence which encodes traceable fusion protein eGFP-GR-TR216. The sequence includes the following features at the indicated nucleotide positions:

EGFP (1-717) GA Linker (718-747) hGR (748-2400) hTR (2401-3141) ATGGTGAGCAAGGGCGAGGAGCTGTTCACCGGGGTGGTGCCCATCCTGGTCGAGCTGGAC GGCGACGTAAACGGCCACAAGTTCAGCGTGTCCGGCGAGGGCGAGGGCGATGCCACCTAC GGCAAGCTGACCCTGAAGTTCATCTGCACCACCGGCAAGCTGCCCGTGCCCTGGCCCACC CTCGTGACCACCCTGACCTACGGCGTGCAGTGCTTCAGCCGCTACCCCGACCACATGAAG CAGCACGACTTCTTCAAGTCCGCCATGCCCGAAGGCTACGTCCAGGAGCGCACCATCTTC TTCAAGGACGACGGCAACTACAAGACCCGCGCCGAGGTGAAGTTCGAGGGCGACACCCTG GTGAACCGCATCGAGCTGAAGGGCATCGACTTCAAGGAGGACGGCAACATCCTGGGGCAC AAGCTGGAGTACAACTACAACAGCCACAACGTCTATATCATGGCCGACAAGCAGAAGAAC GGCATCAAGGTGAACTTCAAGATCCGCCACAACATCGAGGACGGCAGCGTGCAGCTCGCC GACCACTACCAGCAGAACACCCCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCAC TACCTGAGCACCCAGTCCGCCCTGAGCAAAGACCCCAACGAGAAGCGCGATCACATGGTC CTGCTGGAGTTCGTGACCGCCGCCGGGATCACTCTCGGCATGGACGAGCTGTACAAGGGC GCTGGAGCAGGGGCTGGAGCCGGAGCTGACTCCAAAGAATCATTAACTCCTGGTAGAGAA GAAAACCCCAGCAGTGTGCTTGCTCAGGAGAGGGGAGATGTGATGGACTTCTATAAAACC CTAAGAGGAGGAGCTACTGTGAAGGTTTCTGCGTCTTCACCCTCACTGGCTGTCGCTTCT CAATCAGACTCCAAGCAGCGAAGACTTTTGGTTGATTTTCCAAAAGGCTCAGTAAGCAAT GCGCAGCAGCCAGATCTGTCCAAAGCAGTTTCACTCTCAATGGGACTGTATATGGGAGAG ACAGAAACAAAAGTGATGGGAAATGACCTGGGATTCCCACAGCAGGGCCAAATCAGCCTT TCCTCGGGGGAAACAGACTTAAAGCTTTTGGAAGAAAGCATTGCAAACCTCAATAGGTCG ACCAGTGTTCCAGAGAACCCCAAGAGTTCAGCATCCACTGCTGTGTCTGCTGCCCCCACA GAGAAGGAGTTTCCAAAAACTCACTCTGATGTATCTTCAGAACAGCAACATTTGAAGGGC CAGACTGGCACCAACGGTGGCAATGTGAAATTGTATACCACAGACCAAAGCACCTTTGAC ATTTTGCAGGATTTGGAGTTTTCTTCTGGGTCCCCAGGTAAAGAGACGAATGAGAGTCCT TGGAGATCAGACCTGTTGATAGATGAAAACTGTTTGCTTTCTCCTCTGGCGGGAGAAGAC GATTCATTCCTTTTGGAAGGAAACTCGAATGAGGACTGCAAGCCTCTCATTTTACCGGAC ACTAAACCCAAAATTAAGGATAATGGAGATCTGGTTTTGTCAAGCCCCAGTAATGTAACA CTGCCCCAAGTGAAAACAGAAAAAGAAGATTTCATCGAACTCTGCACCCCTGGGGTAATT AAGCAAGAGAAACTGGGCACAGTTTACTGTCAGGCAAGCTTTCCTGGAGCAAATATAATT GGTAATAAAATGTCTGCCATTTCTGTTCATGGTGTGAGTACCTCTGGAGGACAGATGTAC CACTATGACATGAATACAGCATCCCTTTCTCAACAGCAGGATCAGAAGCCTATTTTTAAT GTCATTCCACCAATTCCCGTTGGTTCCGAAAATTGGAATAGGTGCCAAGGATCTGGAGAT GACAACTTGACTTCTCTGGGGACTCTGAACTTCCCTGGTCGAACAGTTTTTTCTAATGGC TATTCAAGCCCCAGCATGAGACCAGATGTAAGCTCTCCTCCATCCAGCTCCTCAACAGCA ACAACAGGACCACCTCCCAAACTCTGCCTGGTGTGCTCTGATGAAGCTTCAGGATGTCAT TATGGAGTCTTAACTTGTGGAAGCTGTAAAGTTTTCTTCAAAAGAGCAGTGGAAGGACAG CACAATTACCTATGTGCTGGAAGGAATGATTGCATCATCGATAAAATTCGAAGAAAAAAC TGCCCAGCATGCCGCTATCGAAAATGTCTTCAGGCTGGAATGAACCTGGAAGCTCGAAAA ACAAAGAAAAAAATAAAAGGAATTCAGCAGGCCACTACAGGAGTCTCACAAGAAACCTCT GAAAATCCTGGTAACAAAACAATAGTTCCTGCAACGTTACCACAACTCACCCCTACCCTG GTGTCACTGTTGGAGGTTATTGAACCTGAAGTGTTATATGCAGGATATGATAGCTCTGTT GACGAGGAATGGGAGCTCATCAAAACTGTCACCGAAGCCCATGTGGCGACCAACGCCCAA GGCAGCCACTGGAAGCAAAAACGGAAATTCCTGCCAGAAGACATTGGACAAGCACCAATA GTCAATGCCCCAGAAGGTGGAAAGGTTGACTTGGAAGCCTTCAGCCATTTTACAAAAATC ATCACACCAGCAATTACCAGAGTGGTGGATTTTGCCAAAAAGTTGCCTATGTTTTGTGAG CTGCCATGTGAAGACCAGATCATCCTCCTCAAAGGCTGCTGCATGGAGATCATGTCCCTT CGCGCTGCTGTGCGCTATGACCCAGAAAGTGAGACTTTAACCTTGAATGGGGAAATGGCA GTGACACGGGGCCAGCTGAAAAATGGGGGTCTTGGGGTGGTGTCAGACGCCATCTTTGAC CTGGGCATGTCTCTGTCTTCTTTCAACCTGGATGACACTGAAGTAGCCCTCCTTCAGGCC GTCCTGCTGATGTCTTCAGATCGCCCGGGGCTTGCCTGTGTTGAGAGAATAGAAAAGTAC CAAGATAGTTTCCTGCTGGCCTTTGAACACTATATCAATTACCGAAAACACCACGTGACA CACTTTTGGCCAAAACTCCTGATGAAGGTGACAGATCTGCGGATGATAGGAGCCTGCCAT GCCAGCCGCTTCCTGCACATGAAGGTGGAATGCCCCACAGAACTCTTCCCCCCTTTGTTC TTGGAAGTGTTCGAGGATTAA

SEQ ID NO: 8 is the amino acid sequence of traceable fusion protein eGFP-GR-TR216. The sequence includes the following features at the indicated amino acid positions:

EGFP (1-290) GA Linker (240-249) hGR (250-800) hTR (801-1046) MVSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPT LVTTLTYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTL VNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLA DHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITLGMDELYKG AGAGAGAGADSKESLTPGREENPSSVLAQERGDVMDFYKTLRGGATVKVSASSPSLAVAS QSDSKQRRLLVDFPKGSVSNAQQPDLSKAVSLSMGLYMGETETKVMGNDLGFPQQGQISL SSGETDLKLLEESIANLNRSTSVPENPKSSASTAVSAAPTEKEFPKTHSDVSSEQQHLKG QTGTNGGNVKLYTTDQSTFDILQDLEFSSGSPGKETNESPWRSDLLIDENCLLSPLAGED DSFLLEGNSNEDCKPLILPDTKPKIKDNGDLVLSSPSNVTLPQVKTEKEDFIELCTPGVI KQEKLGTVYCQASFPGANIIGNKMSAISVHGVSTSGGQMYHYDMNTASLSQQQDQKPIFN VIPPIPVGSENWNRCQGSGDDNLTSLGTLNFPGRTVFSNGYSSPSMRPDVSSPPSSSSTA TTGPPPKLCLVCSDEASGCHYGVLTCGSCKVFFKRAVEGQHNYLCAGRNDCIIDKIRRKN CPACRYRKCLQAGMNLEARKTKKKIKGIQQATTGVSQETSENPGNKTIVPATLPQLTPTL VSLLEVIEPEVLYAGYDSSVDEEWELIKTVTEAHVATNAQGSHWKQKRKFLPEDIGQAPI VNAPEGGKVDLEAFSHFTKIITPAITRVVDFAKKLPMFCELPCEDQIILLKGCCMEIMSL RAAVRYDPESETLTLNGEMAVTRGQLKNGGLGVVSDAIFDLGMSLSSFNLDDTEVALLQA VLLMSSDRPGLACVERIEKYQDSFLLAFEHYINYRKHHVTHFWPKLLMKVTDLRMIGACH ASRFLHMKVECPTELFPPLFLEVFED*

SEQ ID NOs: 9-22 are the following primer sequences used for Q-PCR analysis:

SEQ ID Sequence NO: Mouse cells (3134) Per1 For CTTCTGGCAATGGCAAGGACTC  9 Per1 Rev CAGCATCATGCCATCATACACACA 10 Tgm2 For TGTCACCAGGGATGAGAGACGG 11 Tgm2 Rev TCCAAATCACACCTCTCCAGGAG 12 Lcn2 For ACCTCTCATTTCTTGCAGTTCCG 12 Lcn2 Rev CAGGATGGAGGTGACATTGTAGCT 13 β-Actin For AGTGTGACGTTGACATCCGTA 15 β-Actin Rev GCCAGAGCAGTAATCTCCTTCT 16 Human cells (LNCaP) hNKX3.1 For TGACAGTGGGCTGTTTGTTC 17 hNKX3.1 Rev AAGACCCCAAGTGCCTTTCT 18 hRHOU For TTTCAAGGATGCTGGCTCTT 19 hRHOU Rev GGCCTCAGCTTGTCAAATTC 20 GAPDH For AAGGTGAAGGTCGGAGTCAAC 21 GAPDH Rev GGGGTCATTGATGGCAACAATA 22

DETAILED DESCRIPTION I. Abbreviations

-   AhR aryl hydrocarbon receptor -   AR androgen receptor -   ATRA all-trans retinoic acid -   CAR constitutive androstane receptor -   cst corticosterone -   dex dexamethasone -   ER estrogen receptor protein (α, β) -   ERR estrogen-related receptor (α, β, γ) -   FP fluorescent protein -   FXR farnesoid X receptor -   GCNF germ cell nuclear factor -   GFP green fluorescent protein -   GFP-AhR chimera w/aryl hydrocarbon receptor and GFP -   GFP-AR chimera w/androgen receptor and GFP -   GFP-GR chimera w/ GR (or GR*) and GFP (also, GR-GFP) -   GFP-GR-ER chimera w/ GR translocation domain, estrogen receptor, and     GFP -   GFP-GR-RAR chimera w/ GR translocation domain, retinoic acid     receptor, and GFP

GFP-GR-TR chimera w/ GR translocation domain, thyroid hormone receptor, and GFP

-   GFP-PR-B chimera w/ GR translocation domain, progesterone B     receptor, and GFP -   GR glucocorticoid receptor -   GR* modified GR with increased ligand binding affinity -   HNF4 hepatocyte nuclear factor-4 (α, γ) -   Hsp heat shock protein -   LBD ligand binding domain (of a receptor protein) -   LCA lithocholic acid -   LRH-1 liver receptor homolog-1 -   LTR long terminal repeat -   LXR liver X receptor (α, β) -   MR mineralocorticoid receptor -   MMTV mouse mammary tumor virus -   NF1 nuclear factor 1 -   NHRs nuclear hormone receptors -   NRNC Nuclear Receptors Nomenclature Committee -   OTF1 octomer transcription factor 1 -   POCIS polar organic chemical integrative samplers -   PPAR peroxisome proliferator-activated receptor (α, β/δ, γ) -   PR progesterone receptor -   PXR pregnane X receptor -   RAR retinoic acid receptor -   ROR RAR-related orphan receptor (α, β, γ) -   RRE Rev Responsive Element -   RxR retinoid-X receptor (α, β, γ) -   SF1 steroidogenic factor 1 -   SHP small heterodimer partner -   SRC1 steroid receptor coactivator 1 -   TR thyroid hormone receptor (α, β) -   T₃ triiodothyronine -   T₄ thyroxine -   UDCA ursodeoxycholic acid -   VDR vitamin D receptor -   WWTP waste water treatment plant

II. Terms

Unless otherwise noted, technical terms are used according to conventional usage. In order to facilitate review of the various embodiments of the invention, the following explanations of specific terms are provided:

Cell-based System: A system based employing live cells derived, isolated, or otherwise acquired from a living organism. This term includes, for example, a cell culture.

Chimera/Chimeric: A recombinant nucleic acid molecule generated by cloning portion(s) of one or more nucleic acid sequence(s) in-frame to one or more other nucleic acid sequence(s) to produce a single nucleic acid sequence capable of being transcribed into a polypeptide. A polypeptide expressed from such a nucleic acid sequence chimera is referred to as a “chimeric protein” or “protein chimera”.

Contacting: To place in direct physical association, including in solid or in liquid form. Contacting can occur in vivo, for example by administering an agent to a subject, or in vitro for example with isolated cells or cell-cultures.

Control: Samples believed to be normal (e.g., representative of an activity or function in the absence of the variable being tested), as well as laboratory values, even though possibly arbitrarily set, keeping in mind that such values can vary from laboratory to laboratory. A control sample or group is practically identical to the test sample or group, except for the variable(s) of interest the effect of which is being tested, which is only applied to or found in the test group. A difference between a test sample and a control can be an increase or a decrease. The difference can be a qualitative difference or a quantitative difference, for example a statistically significant difference. In some examples, a difference is an increase or decrease, relative to a control, of at least about 10%, such as at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least about 100%, at least about 150%, at least about 200%, at least about 250%, at least about 300%, at least about 350%, at least about 400%, at least about 500%, or greater than 500%.

Detect: To determine if an agent (such as a bacterium) is present or absent. In some examples this can further include quantification. For example, use of the disclosed methods permits detection of one or more target bacterium, such as by flow cytometry or fluorescence microscopy. Detection can be in bulk, so that a macroscopic number of molecules can be observed contemporaneously or simultaneously. Detection can also include detection of single events, such as a single bacterium.

Emission or emission signal: The light of a particular wavelength generated from a source. In particular examples, an emission signal is emitted from a fluorophore, such as a fluorescent protein, after the fluorophore absorbs light at its excitation wavelength(s).

Environmental sample: A sample obtained from the environment, for instance a water sample (e.g., of surface, sub-surface (ground), rain, run-off, well, spring, drinking, river, estuary, ocean, effluent, treated or untreated sewage, etc. water), soil sample (including soil samples that contain water), air sample, or a sample of another substance.

Excitation or excitation signal: The light of a particular wavelength necessary and/or sufficient to excite an electron transition to a higher energy level. In particular examples, an excitation is the light of a particular wavelength necessary and/or sufficient to excite a fluorophore, such as a fluorescent protein, to a state such that the fluorophore will emit a different (such as a longer) wavelength of light then the wavelength of light from the excitation signal.

Fluorescent property: A characteristic of a fluorescent molecule, such as a fluorescent protein, for example green fluorescent protein, red fluorescent protein, yellow fluorescent protein, cyan fluorescent protein and the like. Examples of fluorescent properties include the molar extinction coefficient at an appropriate excitation wavelength, the fluorescence quantum efficiency, the shape of the excitation spectrum or emission spectrum (the “fluorescence spectrum,” the excitation wavelength maximum and emission wavelength maximum, the ratio of excitation amplitudes at two different wavelengths, the ratio of emission amplitudes at two different wavelengths, the excited state lifetime, or the fluorescence anisotropy. Quantifying fluorescence refers to the determination of the amount of fluorescence generated by a fluorophore, for example a fluorescent protein, which can be the quantity of photons emitted by a fluorophore. In some examples, fluorescence is quantified by measuring the intensity of a fluorescence signal at a particular wavelength, for example the wavelength of the emission maxima of a particular fluorophore, such as a fluorescent protein. Fluorescence intensity can also be quantified at a wavelength that is not the emission maxima of a particular fluorophore, for example to avoid emission spectra that overlap and thereby interfere with the emission maxima of a particular fluorophore, such as a particular fluorescent protein. In some examples, a fluorescence signal is emitted by a population of fluorescent proteins, for example fluorescent proteins present in a population of cells containing such fluorescent proteins. Such a signal can be quantified, for example to determine the number, or relative number of cells that emit such a fluorescent signal. Detecting a pattern of fluorescence refers to the correlation of a fluorescent signal to a specific location to determine the location where a fluorescence signal, such as a fluorescent signal of a particular wavelength, originates. In some examples, a pattern of fluorescence determines the location and or shape of the cells that emit a fluorescence signal, such as cells containing a fluorescent protein, including for example to sub-cellular localization of the fluorescent protein (e.g., cytoplasmic or nuclear) as well as the absolute or relative quantitative distribution between sub-cellular compartments and organelles.

Fluorescent protein: A protein capable of emission of a detectable (and therefore traceable) fluorescent signal. Fluorescent proteins can be characterized by the wavelength of their emission spectrum. For example, wildtype green fluorescent protein (GFP) has a fluorescent emission spectrum in the green part of the visible spectrum. In addition to green-fluorescent proteins, fluorescent proteins are well known that fluoresce in other regions of the visible spectrum, for example blue-fluorescent proteins, cyan-fluorescent proteins, yellow-fluorescent proteins, orange-fluorescent proteins, red-fluorescent proteins, and far-red fluorescent proteins. Non-limiting examples of fluorescent proteins can be found in the following patent documents: U.S. Pat. Nos. 5,804,387; 6,090,919; 6,096,865; 6,054,321; 5,625,048; 5,874,304; 5,777,079; 5,968,750; 6,020,192; 6,146,826; 6,969,597; 7,150,979; 7,157,565; and 7,166,444; and published international patent applications WO 07/085,923; WO 07/052,102, WO 04/058973, WO 04/044203, WO 03/062270; and WO 99/64592. Additional examples of fluorescent proteins are available from Clontech, Laboratories, Inc. (Mountain View, Calif.) under the trade name Living Colors®. Nucleic acids encoding such fluorescent proteins can be incorporated into mammalian expression vectors for use in producing the disclosed fluorescent traceable proteins and fluorescent cell-lines.

Fusion protein: Proteins that have at least two domains fused together, at least one domain comprising traceable (marker) feature (such as a fluorescent protein domain) and another domain or set of domains that provides translocation of the fusion protein from one cellular compartment or organelle to another in a cell in which it is expressed upon the specific binding of a ligand (EDC) to the fusion protein. Optionally the translocation and ligand binding features may be provided from the same source protein (e.g., in a GFP-GR traceable translocation fusion protein). In other embodiments, the translocation and ligand binding features are provided from two different source proteins (thus making a “chimeric receptor” portion of the fusion protein), such that the resultant traceable translocating fusion protein contains domains or subdomains from at least three different source proteins. An example of such a three-component fusion protein is the GFP-GR-ER protein which contains GFP, translocating features of or derived from GR, and the ligand binding domain of an estrogen receptor.

In general, the domains of the disclosed fusions are genetically fused together, in that nucleic acid molecules that encode each protein domain (or subdomain) are functionally linked together, for instance directly or through the use of a linker oligonucleotide, thereby producing a single fusion-encoding (chimeric) nucleic acid molecule. The translated product of such a fusion-encoding (chimeric) nucleic acid molecule is the traceable translocating fusion protein.

High throughput technique: A fast, automated or semi-automated analysis process, for instance to analyze many samples at once in order to detect or measure the presence (or absence) of a substance. In certain examples, combining modern robotics, data processing and control software, liquid handling devices, and sensitive detectors, high throughput techniques allows the rapid screening of many (e.g., hundreds or thousands) samples in a short period of time and often in a highly parallel manner.

Traceable marker protein domain: A protein domain that is detectable based on its inherent structural or functional characteristics, such as fluorescence.

Nuclear hormone receptor family: Nuclear hormone receptors (NHRs) function as ligand-activated transcription factors and have roles in diverse cellular processes ranging from mammalian development and differentiation to metabolic homeostasis (Mangelsdorf et al., Cell, 83(6):835-839, 1995; Adams et al., Science, 287:2185-2195, 2000). NHRs bind to sequence-specific DNA response elements on target gene promoters as homodimers, heterodimers, or monomers. Structural and functional analyses of the NHR family have demonstrated that the receptors are comprised of functional modular domains. The DNA binding domain (DBD) consists of a well characterized zinc finger motif which recognizes a degenerate six to eight nucleotide sequence on the target DNA. The ligand binding domain (LBD) resides in the C-terminal portion of the protein and shares a common, predominantly alpha helical fold (Mangelsdorf et al., Cell, 83(6):835-839, 1995). As implied, this domain of the receptor is where cognate ligands of the receptors interact and induce conformational changes associated with transcriptional activation. Many of the known ligands for these receptors are essential metabolic products including retinoids, thyroid hormone, vitamin D3, bile acids, oxysterols, and prostenoids that act through their cognate receptors to control metabolic homeostasis in the body (Gudas, J. Biol. Chem., 269(22):15399-15402, 1994). In addition, NHRs are also instrumental in the ability of the body to respond to and adapt to complex environmental cues.

Nucleic acid: A polymer composed of nucleotide units (ribonucleotides, deoxyribonucleotides, related naturally occurring structural variants, and synthetic non-naturally occurring analogs thereof) linked via phosphodiester bonds, related naturally occurring structural variants, and synthetic non-naturally occurring analogs thereof. Non-naturally occurring synthetic analogs include, for example and without limitation, phosphorothioates, phosphoramidates, methyl phosphonates, chiral-methyl phosphonates, 2-O-methyl ribonucleotides, peptide-nucleic acids (PNAs), and the like. Such polynucleotides can be synthesized, for example, using an automated DNA synthesizer. The term “oligonucleotide” typically refers to short polynucleotides, generally no greater than about 50 nucleotides. It will be understood that when a nucleotide sequence is represented by a DNA sequence (i.e., A, T, G, C), this also includes an RNA sequence (i.e., A, U, G, C) in which “U” replaces “T.”

Conventional notation is used herein to describe nucleotide sequences: the left-hand end of a single-stranded nucleotide sequence is the 5′-end; the left-hand direction of a double-stranded nucleotide sequence is referred to as the 5′-direction. The direction of 5′ to 3′ addition of nucleotides to nascent RNA transcripts is referred to as the transcription direction. The DNA strand having the same sequence as an mRNA is referred to as the “coding strand;” sequences on the DNA strand having the same sequence as an mRNA transcribed from that DNA and which are located 5′ to the 5′-end of the RNA transcript are referred to as “upstream sequences;” sequences on the DNA strand having the same sequence as the RNA and which are 3′ to the 3′ end of the coding RNA transcript are referred to as “downstream sequences.”

“cDNA” refers to a DNA that is complementary or identical to an mRNA, in either single stranded or double stranded form.

“Encoding” refers to the inherent property of specific sequences of nucleotides in a polynucleotide, such as a gene, a cDNA, or an mRNA, to serve as templates for synthesis of other polymers and macromolecules in biological processes having either a defined sequence of nucleotides (i.e., rRNA, tRNA and mRNA) or a defined sequence of amino acids and the biological properties resulting therefrom. Thus, a gene encodes a protein if transcription and translation of mRNA produced by that gene produces the protein in a cell or other biological system. Both the coding strand (the nucleotide sequence of which is identical to the mRNA sequence and is usually provided in sequence listings) and non-coding strand (used as the template for transcription) of a gene or cDNA can be referred to as encoding the protein or other product of that gene or cDNA. Unless otherwise specified, a “nucleotide sequence encoding an amino acid sequence” includes all nucleotide sequences that are degenerate versions of each other and that encode the same amino acid sequence. Nucleotide sequences that encode proteins and RNA may include introns.

A first sequence is an “antisense” with respect to a second sequence if a polynucleotide whose sequence is the first sequence specifically hybridizes with a polynucleotide whose sequence is the second sequence.

Terms used to describe sequence relationships between two or more nucleotide sequences or amino acid sequences include “reference sequence,” “selected from,” “comparison window,” “identical,” “percentage of sequence identity,” “substantially identical,” “complementary,” and “substantially complementary.”

Operably linked: A first nucleic acid sequence is operably linked with a second nucleic acid sequence when the first nucleic acid sequence is placed in a functional relationship with the second nucleic acid sequence. For instance, a promoter is operably linked to a coding sequence (for example a coding sequence of an antibody or fragment therefore herein disclosed) if the promoter affects the transcription or expression of the coding sequence. Generally, operably linked DNA sequences are contiguous and, where necessary to join two protein-coding regions, in the same reading frame.

ORF (open reading frame): A series of nucleotide triplets (codons) coding for amino acids without any termination codons. These sequences are usually translatable into a peptide. In some examples an open reading frame encodes an antibody or antibody fragment, such as those disclosed herein.

Polypeptide: A polymer in which the monomers are amino acid residues that are joined together through amide bonds, for example γ amide bonds (for example from the γ position of a glutamic acid side chain) or a amide bonds. When the amino acids are alpha-amino acids, either the L-optical isomer or the D-optical isomer can be used. The terms “polypeptide” or “protein” as used herein is intended to encompass any amino acid sequence and include modified sequences such as glycoproteins. The term “polypeptide” is specifically intended to cover naturally occurring proteins, as well as those that are recombinantly or synthetically produced.

The term “polypeptide fragment” refers to a portion of a polypeptide which exhibits at least one useful epitope. The term “functional fragments of a polypeptide” refers to all fragments of a polypeptide that retain an activity of the polypeptide. Biologically functional fragments, for example, can vary in size from a polypeptide fragment as small as an epitope capable of binding an antibody molecule to a large polypeptide capable of participating in the characteristic induction or programming of phenotypic changes within a cell.

Sample: A material to be analyzed, for example to determine if it contains one or more target bacteria. Includes but is not limited to biological samples (e.g., obtained from a human or veterinary subject); food samples (e.g., vegetable, dairy, fruit or meat sample); environmental samples (e.g., soil, air, water, surfaces), and the like.

Sewage: Water-based fluid containing organic matter and solutes. Sewage may include feces and urine from human and non-human animals. Sewage may include waste from human activities, for example, blackwater (e.g., toilet and dishwasher waste) and grey water (e.g. waste water generated from washing activities). Residential, institutional, commercial and industrial establishments may produce sewage, including waste from toilets, baths, showers, kitchens, sinks, etc. Typically, sewage is waste intended to be carried away from the source of the waste, for example, carried to a sewage treatment facility.

Receptor Superfamily: Family of steroid, nuclear, and orphan receptor proteins having an identifiable ligand binding domain. The term as used herein is intended to encompass the known classic nuclear receptors, hormone receptors, and orphan receptors, as well as proteins having an identifiable ligand binding domain which may discovered in the future.

TABLE 1 Representative Nuclear Receptors Sub- family and NR/ Accession Group Gene Literature Names Number 1A NR1A1 TRα, c-erbA-1, THRA M24748 NR1A2 TRβ, c-erbA-2, THRB X04707 1B NR1B1 RARα X06538 NR1B2 RARβ, HAP Y00291 NR1B3 RARγ, RARD M57707 1C NR1C1 PPARα L02932 NR1C2 PPARβ, NUC1, PPARδ, FAAR L07592 NR1C3 PPARγ L40904 1D NR1D1 REVERBα, EAR1, EAR1A M24898 NR1D2 REVERBβ, EAR1β, BD73, RVR, HZF2 L31785 NR1D3 E75 X51548 1E NR1E1 E78, DR-78 U01087 IF NR1F1 RORα, RZRα U04897 NR1F2 RORβ, RZRβ Y08639 NR1F3 RORγ, TOR U16997 NR1F4 HR3, DHR3, MHR3, GHR3, CNR3, M90806 CHR3 U13075 1G NR1G1 CNR14 U13074 1H NR1H1 ECR M74078 NR1H2 UR, OR-1, NER1, RIP15, LXRβ U07132 NR1H3 RLD1, LXR, LXRα U22662 NR1H4 FXR, RIP14, HRR1 U09416 1I NR1I1 VDR J03258 NR1I2 ONR1, PXR, SXR, BXR X75163 NR113 MB67, CAR1, CARα Z30425 NR1I4 CAR2, CARβ AF00932 1J NR1J1 DHR96 U36792 1K NR1K1 NHR1 U19360 2A NR2A1 HNF4 X76930 NR2A2 HNF4G Z49826 NR2A3 HNF4B Z49827 NR2A4 DHNF4, HNF4D U70874 2B NR2B1 RXRA X52773 NR2B2 RXRB, H-2RIIBP, RCoR-1 M84820 NR2B3 RXRG X66225 NR2B4 USP, Ultraspiracle, 2C1, CF1 X52591 2C NR2C1 TR2, TR2-11 M29960 NR2C2 TR4, TAK1 L27586 2D NR2D1 DHR78 U36791 2E NR2E1 TLL, TLX, XTLL S72373 NR2E2 TLL, Tailless M34639 2F NR2F1 COUP-TFI, COUPTFA, EAR3, SVP44 X12795 NR2F2 COUP-TFII, COUPTFB, ARP1, SVP40 M64497 NR2F3 SVP, COUP-TF M28863 NR2F4 COUP-TFIII, COUPTFG X63092 NR2F5 SVP46 X70300 NR2F6 EAR2 X12794 3A NR3A1 ERα X03635 NR3A2 ERβ U57439 3B NR3B1 ERR1, ERRα X51416 NR3B2 ERR2, ERRβ X51417 3C NR3C1 GR X03225 NR3C2 MR M16801 NR3C3 PR M15716 NR3C4 AR M20132 4A NR4A1 NGFIB, TR3, N10, NUR77, NAK1 L13740 NR4A2 NURR1, NOT, RNR1, HZF-3, TINOR X75918 NR4A3 NOR1, MINOR D38530 NR4A4 DHR38, NGFIB U36762 CNR8, C48D5 U13076 5A NR5A1 SF1, ELP, FTZ-F1, AD4BP D88155 NR5A2 LRH1, xFF1rA, xFF1rB, FFLR, PHR, FTF U93553 NR5A3 FTZ-F1 M63711 5B NR5B1 DHR39, FTZF1B L06423 6A NR6A1 GCNF1, RTR U14666 0A NR0A1 KNI, Knirps X13331 NR0A2 KNRL, Knirps related X14153 NR0A3 EGON, Embryonic gonad, EAGLE X16631 NR0A4 ODR7 U16708 NR0A5 Trithorax M31617 0B NR0B1 DAX1, AHCH S74720 NR0B2 SHP L76571 ^(#) Derived from A unified nomenclature system for the nuclear receptor superfamily (Nuclear Receptors Nomenclature Committee, Cell 97(2):161-163, 1999).

Unless otherwise explained, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The singular terms “a,” “an,” and “the” include plural referents unless context clearly indicates otherwise. Similarly, the word “or” is intended to include “and” unless the context clearly indicates otherwise. Hence “comprising A or B” means including A, or B, or A and B. It is further to be understood that all base sizes or amino acid sizes, and all molecular weight or molecular mass values, given for nucleic acids or polypeptides are approximate, and are provided for description. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, suitable methods and materials are described below. All publications, patent applications, patents, sequences defined by accession number, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including explanations of terms, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.

III. Overview of Several Embodiments

Provided herein in a first set of embodiments are systems for detecting or quantifying a ligand (e.g., an agonist or an antagonist) of a superfamily receptor protein in an environmental sample. In examples thereof, the system comprises a first mammalian cell expressing a first traceable fusion protein; a second mammalian cell expressing a second traceable fusion protein; and a detection system for the detection of the cytoplasm-to-nuclear translocation of the marker proteins, wherein the first and second traceable fusion proteins independently comprise either: (1) a superfamily receptor protein, and a marker protein domain; or (2) the cytoplasmic/nuclear translocation domain of glucocorticoid receptor, the ligand binding domain of a superfamily receptor protein, and a marker protein domain. Optionally, the mammalian cells are human cells.

In examples of the described system for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample, the first traceable fusion protein binds a different ligand than the second traceable fusion protein.

In examples of the described system for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample, the marker protein domain is different in the first and second traceable fusion proteins. This enables differential detection of the two fusion proteins, for instance in the same analysis system or sample.

In any of the described system for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample, the marker protein domain may optionally be a fluorescent protein domain.

Also described are systems for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample, wherein the ligand for the first or second traceable fusion protein is a natural ligand for the superfamily receptor protein of the traceable fusion protein, or a natural or synthetic compound that binds competitively therewith.

Also provided are systems for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample that additionally comprise one or more compounds and/or compositions that stably associate with a traceable fusion protein in the absence of a ligand for the ligand binding domain of the traceable fusion protein, and which dissociates from the fusion protein in the presence of a ligand for the ligand binding domain of the traceable fusion protein.

Yet another embodiment provides a system for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample, which system includes at least four mammalian cell lines each expressing a different traceable fusion protein, wherein at least one traceable fusion protein binds a glucocorticoid, at least one traceable fusion protein binds an androgen, at least one traceable fusion protein binds a progestin, and at least one traceable fusion protein binds an aryl hydrocarbon.

The systems described herein are optionally provided as kits.

Also described are methods for detecting or quantifying an endocrine disruptor chemical (EDC) ligand in an environmental sample, which methods involve contacting with the environmental sample a human cell expressing in its cytoplasm a fusion protein comprising: a receptor for the ligand, which receptor translocates from the cytoplasm to the nucleus upon ligand binding; and a marker protein domain; and then detecting cytoplasmic to nuclear translocation of the fusion protein in response to a ligand of the ligand binding domain in the water sample.

Also described are methods of determining the concentration of an endocrine disruptor chemical (EDC) ligand in an environmental sample, which methods involve contacting with the environmental sample a population of eukaryotic cells expressing in their cytoplasm a fusion protein comprising: a receptor for the ligand, which receptor translocates from the cytoplasm to the nucleus upon ligand binding; and a marker protein domain; and scanning one or more test cell(s) to obtain signal data from the marker of the fusion protein; converting the signal data to obtain the cellular location of the labeled protein in the test cell(s); and analyzing the signal data using an analysis system having an algorithm to calculate changes in distribution of the labeled fusion protein between the cytoplasm and the nucleus of the test cell(s), the analysis system having the capability of providing an accurate reading of the concentration of the ligand.

In any of the provided systems, kits, and methods, the environmental sample can include a water sample, soil sample, or air sample. By way of example, where the environmental sample comprises a water sample, the sample includes in various embodiments one or more of surface water, sub-surface (ground) water, rain, run-off, well water, spring water, drinking water (processed or not), river water, estuary water, ocean water, effluent, treated sewage or untreated sewage.

Yet further embodiments are described herein.

IV. Systems and Kits for Detection of EDCs

Disclosed herein is use of a highly sensitive cytoplasm-to-nucleus translocation assay to monitor one or more EDC level or activity, for instance in water samples. A high throughput screen of water samples is described, using in one example a cell line expressing GFP-tagged glucocorticoid receptor (GR) (GFP-GR); the detected output that signals presence of EDC/ligand (such as glucocorticoid) in the sample is accumulation of fluorescence in the cell nucleus (that is, migration of the fluorescent fusion protein from the cytoplasm into the nucleus). By way of example, an automated imaging system (such as the PerkinElmer Opera® High Content Imaging system) can be used to image the change in fluorescence localization in individual cells; also contemplated are non-automated, direct microscopic examination embodiments.

Though the high-throughput, low cost, high sensitivity EDC detection system is described in detail with regard to a few exemplary traceable cytoplasm-to-nuclear marker proteins, it will be apparent to one of ordinary skill based on the teachings herein that the provided principles can be applied to the detection of other EDC compounds though use of different receptor fusions. Thus, specifically contemplated herein are methods and kits that employ cell lines expressing one or more of the following detector fusions: GFP-GR, GFP-AR, GFP-AhR, GFP-PR-B, GFP-GR-ER, GFP-GR-RAR, and GFP-GR-TR, as well as fusions in which the GFP is replaced with a different fluorescent domain that emits light at a different wavelength. Specifically contemplated are kits that include cell lines expressing two or more traceable fusion, where each is responsive to a different EDC and contains a differentially fluorescing traceable domain. Kits containing multiple cell lines, each of which expresses a different cytoplasm-to-nuclear traceable fusion protein are also contemplated. Also envisioned are GFP fusions to mutant, variant, or modified forms of nuclear receptors that manifest detectable subcellular relocalization in response to ligand.

A. Traceable Translocating Fusion Proteins with Non-Chimeric Receptors

Embodiments provided herein employ cells that express a traceable fusion protein, which changes its sub-cellular localization (for example, translocates from the cytoplasm into the nucleus) upon binding of an EDC ligand compound. Examples of such traceable translocating fusion proteins comprise a traceable marker domain (exemplified by a fluorescent protein domain, such as GFP) functionally fused to a nuclear superfamily receptor domain that is sufficient for both recognition of the EDC ligand and for consequent translocation of the fusion protein from the cytoplasm into the nucleus.

Cell lines expressing other “non-chimeric” receptors (that is, not needing to be fused to the translocation domain of GR) such as GFP-AR (Klokk, et al., Mol. Cell. Biol. 27:1823-1843, 2007), GFP-AhR (Elbi et al., Proc Natl Acad Sci USA 101(9):2876-2881, 2004), GFP-PR-B (Rayasam et al., Mol Cell Biol 25(6):2406-2418, 2005) have been generated previously in our laboratory. In addition to the GFP-GR, which could detect biologically active glucocorticoids in water samples, GFP-AR was used for the detection of androgen activity and positive results were obtained for many of the tested water samples.

A fluorescent protein (or protein domain) is a protein (or portion of a protein) that fluoresces in cells without adding exogenous cofactors. That is, it is a protein that can be expressed in cells and detected in these cells simply by exciting the protein with light and visualizing the resultant fluorescence. An example of such a fluorescent protein is the green fluorescent protein (GFP) originally isolated from the jellyfish Aequorea victoria. Another example of a fluorescent protein as defined herein is the green fluorescent protein originally isolated from Renilla reniforms, which exhibits a single absorption peak at 498 nm and an emission peak at 509 nm (Cubitt et al. TIBS 20: 448-455, 1995). It is also contemplated that modifications may be made to a fluorescent protein, as long as the resulting protein fluoresces when expressed in cells. The art recognizes many modifications that can be (and have been) made to existing fluorescent proteins, for instance to provide different excitation and emission peaks, to increase stability, that speed up the rate of the oxidation step of chromophore formation, that increase brightness at longer wavelengths, and that reduce pohotoisomerization and/or photobleaching.

Optionally, the fusion protein can include a linking peptide sequence between the traceable (e.g., fluorescent protein) domain and the steroid or other receptor domain. For example, a sequence of the amino acids glycine and alanine, or a sequence of alanine alone can be used; however, any sequence of amino acids and any length can be used that does not interfere with the binding of the receptor domain to its response element and that does not prevent fluorescence of the fluorescent protein. Typically, a linker peptide will range from two to about ten amino acids but maybe shorter or longer. Of course, certain linker peptides maybe preferred over others, e.g., the presence of four basic amino acids in a string of six might suffice as a nuclear localization signal so as to mislocate the uninduced state of the factor. A linker peptide can be used to separate the fluorescent protein structurally from the response element and can function to allow the fluorescent protein independently of the remaining portion of the chimeric protein. Typically, the traceable protein domain (e.g., fluorescent protein) can be fused to either the C-terminus or the N-terminus of the ligand receptor domain; however, the preferable construction for any specific fusion protein can readily be determined. Linker peptides can readily be introduced between the two protein domains in the fusion protein by producing a nucleic acid that encodes the fusion protein having the linker sequence between the detectable protein component and ligand responsive/translocation component.

The ligand binding domain (e.g., transcription factor component) of the traceable fusion protein can be derived from any selected mammal. Additionally, fusion proteins utilizing a transcription factor from one mammal can often be used in a cell from another mammal. F or example, the glucocorticoid receptor amino acid sequence is highly conserved, particularly in the binding region among rat, human and mouse, and, for example, the rat glucocorticoid receptor binds with high affinity to the human glucocorticoid response element. However, in various embodiments provided herein, the ligand-binding and/or translocation component(s) of the traceable fusion proteins are based on human proteins.

Additional information regarding the construction of traceable translocating fusion proteins useful in the described methods and kits is provided in WO 97/20931 and U.S. Pat. Nos. 6,455,300, 7,312,032 and 8,058,395, each of which is incorporated by reference herein.

B. Traceable Translocating Fusion Proteins with Chimeric Receptors

Also contemplated are cell lines, methods, systems and kits that employ traceable chimeric receptors, that is traceable receptors that include a portion of a nuclear receptor for example responsible for cytoplasmic/nuclear translocation activity functionally fused to the ligand-binding portion of another superfamily receptor. A representative example is the GR-ER chimera (Martinez et al., J. Ster. Biochem Mol. Biol. 97:307-321, 2005), which contains the rat GR (rGR) N-terminus, DNA binding domain (DBD) and hinge regions upstream of a hybrid ligand binding domain (LBD) composed of GR helix 1 and partial loop 1-3 sequences linked to human ER alpha (hERα) LBD sequences starting with the C-terminus of loop 1-3.

The construction of examples of such chimeric traceable receptors is described in U.S. Patent Publication No. 2003/0077645, Mackem et al. (J. Biol. Chem. 276(49):45501-45504, 2001), and Martinez et al. (J. Ster. Biochem Mol. Biol. 97:307-321, 2005), each of which is incorporated herein by reference. These references describe production of fluorescently tagged fusion proteins that contain a chimera between the translocation features of glucocorticoid receptor and another nuclear superfamily receptor, such as the estrogen receptor, a retinoic acid receptor, and so forth. In each case, the labeled chimera is found in the cytoplasm in the absence of its cognate ligand), and is rapidly translocated to the nucleus in a dose-dependent manner upon exposure of the cell to ligand.

C. Additional Chimeric Receptors

GFP-GR (pCI-nGFP-C656G) and GFP-AR (eGFP-hAR) fusion proteins have been published ((Walker et al., Methods (Comp. to Meth. Enzym.) 19:386-393, 1999; Klokk et al., Mol. Cell. Biol. 27:1823-1843, 2007) and have proven useful in detecting biologically active glucocorticoid and androgens in water samples, as described below in Example 1. Additional chimeras (eGFP-GR-ER310 and eGFP-GR-TR216) have been constructed. Mammalian cell lines can be readily prepared which express each of these chimeras under tetracycline regulation. The nucleotide sequences of pCI-nGFP-C656G (SEQ ID NO: 1), eGFP-hAR (SEQ ID NO: 3), eGFP-GR-ER310 (SEQ ID NO: 5), and eGFP-GR-TR216 (SEQ ID NO: 7) are provided.

D. Detection Cell Lines

The methods and kits described herein employ cell lines that express at least one traceable translocating fusion protein as described herein. For detection of the translocation of the labeled fusion protein from one sub-cellular compartment or organelle to another, any eukaryotic cell can be utilized, though mammalian cells and particularly human cells are contemplated. Representative methods for the construction of cell lines useful in the described methods and kits, as well as examples of such cell lines, are provided in WO 97/20931, U.S. Pat. Nos. 6,455,300, 7,312,032 and 8,058,395; U.S. Patent Publication No. 2003/0077645, Mackem et al. (J. Biol. Chem. 276(49):45501-45504, 2001), and Martinez et al. (J. Ster. Biochem Mol. Biol. 97:307-321, 2005), each of which is incorporated by reference herein.

In addition to steroid receptors, there are other ligand-dependent receptors (such as thyroid hormone receptor, retinoic acid receptor, retinoid X receptor, TCCD (dioxin) receptor (AhR), fatty acid activatable receptors, etc.) and stimulus-dependent receptors (such as peroxisome proliferator activated receptor, growth factor-dependent receptors such as epidermal growth factor, nerve growth factor, etc.), and factors (such as CREB, NFAT, NFkB/IkB, etc.), and other receptors whose ligand remains to be defined (such as mammalian homologs of the Drosophila tailless, knirps, sevenup, FTZF1 genes, etc.). Many of these receptors or factors can be found listed in Parker, Steroid Hormone Action (Oxford University Press, New York, pp. 210, 1993), in Tsai & O'Malley (Annu. Rev. Biochem. 63:451-486, 1994), and in GenBank and other publicly available sequence databases, which contain additional receptors as well as the complete nucleotide sequences of the genes and cDNAs.

E. Methods for Detecting and/or Quantifying EDC(s) in Environmental Samples

The present disclosure provides methods of detecting in an environmental sample the presence of an agonist or antagonist of a nuclear superfamily receptor comprising contacting the sample with a cell expressing at least one traceable translocating fusion protein and directly detecting the sub-cellular location of fluorescence (or other appropriate label) within the cell, the location of fluorescence aggregated in the nucleus indicating the presence in the environmental sample of at least one agonist or antagonist of the ligand-binding EDC receptor domain of the traceable translocation fusion protein. In addition to the exemplary methods described herein, methods generally applicable for detecting or quantifying a ligand using a traceable translocation fusion protein can be found in WO 97/20931, U.S. Pat. Nos. 6,455,300, 7,312,032 and 8,058,395; U.S. Patent Publication No. 2003/0077645, Mackem et al. (J. Biol. Chem. 276(49):45501-45504, 2001), and Martinez et al. (J. Ster. Biochem Mol. Biol. 97:307-321, 2005), each of which is incorporated by reference herein.

Direct detection means detection of the fluorescence emitted from the site in the cells when excited by (ultraviolet or visible) light, without the need for any additional chemical reactions or treatment of the cells. The fluorescence is directly detected by any device capable of detecting fluorescence, such as a fluorescent microscope, as visualized by the eye of the operator of the microscope at the time or as recorded from the microscope such as by photography of the field of view or through the use of photosensitive detectors.

A fluorescent microscope, such as a confocal laser scanning microscope or an epifluorescent microscope, can be used, as is known in the art.

There is no requirement that cells be, e.g., fixed or stained or contacted by any additional reagents, in order to detect the translocation. Thus living cells can be assayed, and results obtained, shortly (for instance, about 30 minutes) after being contacted with a test sample. Furthermore, screening nuclear localization of fluorescence (translocation) can readily be adapted to high throughput computerized image analysis. Thus, the analysis of large numbers of samples can be automated, for instance for the repetitive examination of multiple environmental samples (for instance, from multiple sources or locations) as well as for the large-scale screening of sets of samples for multiple EDC contaminants.

Also provided is a method of detecting or monitoring the level of agonists and antagonists of a steroid receptor in an environmental sample, comprising obtaining periodic samples from a source or location over time (e.g., on a daily, weekly, monthly, bi-annually, annually, or longer basis), contacting the samples with cell(s) expressing one or more of the herein-described traceable translocating fusion proteins, and detecting the location of fluorescence within the cells. Optionally, the cells each or collectively express a set of two or more different traceable translocating fusion proteins that are responsive to different ligands (e.g., different EDCs known to or suspected of being contaminants in the environment being sampled). The amount or magnitude of fluorescence migration from the cytoplasm to the nucleus can be compared between the periodic samples, in order to monitor trends (upwards or downwards) in the levels of EDC contamination at a single location or set of locations over time. Decrease in the nuclear translocation in a later-obtained sample relative to an earlier-obtained sample indicating a decrease in level of the EDC agonist or antagonist of the receptor in the sample, while an increase in translocation into the nucleus in a later-obtained sample relative to an earlier-obtained sample indicates an increase in level of the EDC agonist or antagonist of the steroid receptor in the sample.

F. Automated High Throughput Analysis Systems and Image Analysis Software

Described herein is one embodiment of automated high throughput analysis of the presence of EDCs in environmental samples, using the PerkinElmer Opera® High Content Image Screening System and accompanying software package. With this teaching, additional high throughput applications of the herein described EDC detection and measuring methods are now enabled.

Contemplated herein is the use of “arrays” of cells that express one or more traceable translocating fusion protein, which cells are placed into an array such as a microchannel array, microtiter plate or other array system that permits separate cell samples to be contacted separately with different test samples (e.g., environmental samples, such as water samples, to be analyzed for the presence or level of one or more EDCs).

Arrays, as the term is used herein, are arrangements of addressable locations on a substrate; each address may contain a sample of one or more cells or cell lines. A “microarray” is an array that is miniaturized so as to require microscopic examination for evaluation of hybridization or other detection signals. “Macroarrays” are somewhat larger, such that at least the spot at each address is recognizable by the naked human eye. Primary examination for the presence and location of cellular fluorescence (or other traceable signals) in cells of the array is usually carried out using a microscope or other magnifying device.

Within an array, each arrayed cell sample is addressable, in that its location can be reliably and consistently determined within the at least the two dimensions of the array surface. Thus, in ordered arrays the location of each cell sample is assigned to the sample at the time when it is applied to the array and usually a key is provided in order to correlate each location with the appropriate “target” cell sample. Often, ordered arrays are arranged in a symmetrical grid pattern, but samples could be arranged in other patterns (e.g., in radially distributed lines or ordered clusters).

The data generated using an array according to this invention (e.g., subcellular localization of one or more traceable translocating fusion proteins) can be analyzed using computerized systems. For instance, the array can be read by a computerized “reader” or scanner and the quantification of the location traceable signal to individual cells and/or subcellular compartments within cells on the array carried out using computer algorithms. Such analysis of the array can be referred to as “automated detection” in that the data is being gathered by an automated reader system.

In the case of labels that emit detectable electromagnetic waves or particles, the emitted light (e.g., fluorescence or luminescence) or radioactivity can be detected by sensitive cameras, confocal scanners, image analysis devices, radioactive film or a Phosphoimager, which capture the signals (such as a color image or artificial color image) from the array. A computer with image analysis software then detects this image, and analyzes the intensity and/or pattern of the signal for each cell sample location (address), and optionally individual cells within a location, in the array. Signals can be compared between locations on a single array, or between arrays (such as a single array that is sequentially analyzed at different wavelengths in order to detect the localization of different traceable fusion proteins).

Computer algorithms can also be used for comparison between spots on a single array or on multiple arrays. In addition, the data from an array can be stored in a computer readable form.

Certain examples of automated array readers (scanners) will be controlled by a computer and software programmed to direct the individual components of the reader (e.g., mechanical components such as motors, analysis components such as signal interpretation and background subtraction). Optionally software may also be provided reader to control a graphic user interface and one or more systems for sorting, categorizing, storing, analyzing, or otherwise processing the data output of the reader.

By way of example, to “read” an array that contains cells expressing a traceably labeled translocating protein (e.g., a fusion protein that contains a GFP or other fluorescent protein domain), the array can be placed into (or onto, or below, etc., depending on the location of the detector system) the reader and a traceable signal detected by the reader. These detectable signals could be associated with an address identifier signal. The reader gathers information from each of the addresses, associates it with the address identifier signal, and recognizes addresses with a detectable signal (including a particular type of signal, such as relatively intense fluorescence localized to the nucleus of the cell) as distinct from those not producing such a signal (or producing a different kind of signal, such as diffuse fluorescence in the cytoplasm of cells). Certain readers are also capable of detecting intermediate levels of signal, between no signal at all and a high signal, such that quantification of signals at individual addresses is enabled. In particularly beneficial embodiments, the reader is equipped with software that enables it to map individual cells and cell nuclei in order to determine and measure the subcellular localization of the traceable signal.

Certain readers that can be used to collect data from the arrays used with the described methods, especially those that use a fluorescently tagged fusion protein, will include a light source for optical radiation emission. The wavelength of the excitation light will usually be in the UV or visible range, but in some situations may be extended into the infra-red range. A beam splitter can direct the reader-emitted excitation beam into the object lens, which for instance may be mounted such that it can move in the x, y and z directions in relation to the surface of the array substrate. The objective lens focuses the excitation light onto the array, and more particularly onto the (microbial cell) targets on the array. Light at longer wavelengths than the excitation light is emitted from addresses on the array that contain fluorescently-labeled probe molecules (i.e., those addresses containing a cell to which the probe binds).

In certain embodiments of the invention, the array may be movably disposed within the reader as it is being read, such that the array itself moves (for instance, rotates) while the reader detects information from each address. Alternatively, the array may be stationary within the reader while the reader detection system moves across or above or around the array to detect information from the addresses of the array. Specific movable-format array readers are known and described, for instance in U.S. Pat. No. 5,922,617, hereby incorporated in its entirety by reference. Examples of methods for generating optical data storage focusing and tracking signals are also known (see, for example, U.S. Pat. No. 5,461,599).

G. Kits for Screening an Environmental Sample, and Methods of Use Thereof

It is contemplated that the fusion proteins and cells described herein can be used to screen environmental samples for the presence and/or level of one or more EDCs, which methods optionally may be carried out using kits.

In one specific contemplated example, the kits are very simple—comprising one or more water-tight container(s) in which water or other environmental samples are collected (one sample per container). In examples of this embodiment, the containers are substantially non-reactive and contain no chemicals that might be transferred into the collected sample (e.g., by leaching) and thereby detected during subsequent sample analysis. By way of example only, containers may be 500 ml (or smaller) pre-cleaned glass bottles. Optionally, such kits may include system(s) for holding the sample containers (e.g., a rack or other device, including for instance providing the containers as part of a single unit such that two or more containers are joined to each other), including for instance for holding the containers during shipping or other transportation. Sample collection containers may be joined to each other, for instance in a plate or sheet configuration. In some instances, the kits include an acidifying agent that is used to acidify the environmental samples (e.g., to pH ˜3); an example of such acidifying agent is 6N hydrochloric acid (though one of ordinary skill in the art will recognize that other acidifying agents can be used). The kits may also be formatted to permit chilling of samples once they are collected, for instance chilling to about 4° C.

Capture kits of this relatively simple variety may be used in a remote-analysis system, where the samples are obtained from the environment at one location and then transported (e.g., by shipping the collected samples) to a remote location for analysis. Optionally, such kits are formatted so that the samples are shipped cold (e.g., under ice) so as to maintain a temperature of ˜4° C. from soon after collection until the samples are processed for analysis at the remote location (e.g., a centralized analysis center, such as a mail-order analysis site). Kits intended for shipping to a remote analysis site optionally may be provided with mailers, such as pre-paid mailers, and/or instructions for how to ship the samples to the analysis site after collection. It is contemplated that regular sample analysis systems may be employed, for instance where a site is (or set of sites are) sampled on a regular basis and the samples returned to the same analysis site on a daily, weekly, bi-weekly, monthly, quarterly, yearly, or other regular basis. In such instances, for instance where a water processing plant or other utility or agency is taking samples, a shipping system or pick-up/delivery system can be used for transporting the samples from the collection site(s). This may enable highly reliable sample movement, while helping to keep costs down for repeat sample analysis.

Also contemplated are analysis kits, which contemplate and enable the analysis of the sample(s) without needing to engage a remote analysis site. Such kits can be used with the methods described herein to detect (and optionally quantify) one or more EDCs from samples, such as environmental samples. Such analysis kits include (for instance, in addition to one or more components of the capture kits described above—such as sample collection containers) components of a herein described system used to analyze the environmental sample, including for instance one or more (e.g., two, three, four or more) mammalian cell line(s), each of which expresses at least one traceable fusion protein. In one embodiment, the kit implements a system for detecting or quantifying a ligand of a superfamily receptor protein in a water sample, the system comprising a first mammalian cell expressing a first traceable fusion protein, a second mammalian cell expressing a second traceable fusion protein; and (optionally) a detection system for detection of the cytoplasm-to-nuclear translocation of the marker proteins (for instance, detection of the sub-cellular localization of each marker protein), wherein the first and second traceable fusion proteins independently comprise either: (1) a superfamily receptor protein, and a marker protein domain; or (2) the cytoplasmic/nuclear translocation domain of glucocorticoid receptor, the ligand binding domain of a superfamily receptor protein, and a marker protein domain. Optionally, the analysis kit comprises one or more compounds and/or compositions that stably associate with a traceable fusion protein of the kit in the absence of a ligand for the ligand binding domain of the traceable fusion protein, and which compound/composition dissociates from the fusion protein in the presence of a ligand for the ligand binding domain of the traceable fusion protein.

Specifically contemplated are kits that comprising at least four mammalian cell lines each expressing a different traceable fusion protein, wherein at least one traceable fusion protein of the kit binds a glucocorticoid, at least one traceable fusion protein of the kit binds an androgen, at least one traceable fusion protein of the kit binds a progestin, and at least one traceable fusion protein of the kit binds an aryl hydrocarbon.

Optionally, analysis kits provided herein include a portable fluorescence reader programmed to detect and monitor translocation of one or more traceable translocating fusion proteins described herein. Portable in this context may refer to a device that can readily be carried by a person into the field. However, in additional embodiments, the portable fluorescence reader is of a size that requires a transport vehicle, for instance a portable analysis van that can be moved from location to location to provide analysis of environmental samples.

Kits may be provided with instructions, for instance instructions for the collection of environmental samples, instructions for after-collection processing of the samples, for analysis of the samples to detect one or more EDCs using the systems and cells and methods described herein, and so forth. The instructions can provide calibration curves or charts to compare with the determined (e.g., experimentally measured) values.

The following example is provided to illustrate certain particular features and/or embodiments. The example should not be construed to limit the invention to the particular features or embodiments described.

Example 1 Prevalent Glucocorticoid and Androgen Activity in U.S. Water Sources

Contamination of the environment with various endocrine disrupting chemicals (EDCs) is a major health concern. The presence of estrogenic compounds in water and their deleterious effects are well documented. However, effective detection and monitoring of EDCs, including corticosteroids and androgens, is lacking.

Described in this example is use of a highly sensitive live cell assay based on sub-cellular relocalization of green fluorescent protein (GFP)-tagged nuclear receptors, exemplified by the glucocorticoid receptor (GR) and androgen receptor (AR) to test samples from US water sources for hormonal activity. This assay is based on the fact that unoccupied GR resides in the cytoplasm bound to various heat-shock proteins and immunophilins in a large multi-protein complex (Pratt & Tort, Endocr. Rev. 18:306-360, 1997; Pratt et al., Exp. Pharmacol. 111-138, 2006). Upon hormone binding, GR dissociates from the chaperones and translocates to the cell nucleus (FIGS. 1A and 1B), where it interacts with GR regulatory elements (GREs) to elicit GR-specific transcription regulation. This cell based assay is used to monitor glucocorticoid and androgen activity in water samples from more than 100 locations in the Northeast United States. Using cell lines expressing GFP-tagged glucocorticoid and androgen receptors (GFP-GR and GFP-AR, respectively) in high a throughput screening, combined with studies on transcription activation, previously unrecognized glucocorticoid activity was discovered in 27%, and androgen activity in 35%, of all tested water sources from 14 states. In addition to nuclear translocation, water samples induced GR and AR-dependent gene expression. Steroids of both classes impact body development, metabolism, and interfere with reproductive, endocrine, and immune systems. This prevalent contamination could negatively affect wildlife and humans.

The levels of steroidal EDCs in the environment are not efficiently monitored and/or regulated at present. One of the reasons is that a high-throughput, reliable, and low-cost detection methods for monitoring of biologically active steroidal EDCs, including corticosteroids, have not been developed and are in demand (Roy & Pereira, Indian J. Exp. Biol 43:975-992, 2005).

Chemical methods for detection of EDCs reveal the presence of several classes of steroid hormones in water sources in China (Chang et al., Environ. Sci. Technol. 43:7691-7698, 2009). Mass spectrometry data from wastewaters in the Netherlands (Schriks et al., Environ. Sci. Technol. 44:4766-4774, 2010) and also China (Chang et al., Environ. Sci. Technol. 41:3462-3468, 2007) suggest possible contamination with glucocorticoids and a recent study demonstrated that environmentally relevant concentrations of synthetic glucocorticoids have deleterious effects on fish (Kugathas & Sumpter, Environ. Sci. Technol. 45:2377-2383, 2011). However, it is unclear whether in U.S. water sources are also contaminated by EDCs and to what extent. It is also unclear whether the EDCs detected in water sources could elicit steroid-specific biological response(s) in mammalian systems.

Chemical methods for EDCs detection, although sensitive, are expensive, time-consuming, and largely incompatible with a large-scale sample testing. Therefore, it is crucial to develop, test, and implement methods for high-speed, reliable, and low-cost detection of biologically active EDCs in contaminated water and other environmental sources. Here we utilize a highly sensitive cellular assay based on cytoplasm to nucleus translocation to detect glucocorticoid activity in U.S. water sources.

Materials and Methods Samples Collection

Environmental water samples were collected as part of ongoing U.S. Geological Survey (USGS) projects that were implemented to monitor the presence and effects of endocrine-disruptors and other contaminants of emerging concern. They were collected between 2005 and 2010 from different geographic locations in the United States (FIG. 8), and included discrete grab water samples, or samples collected via polar organic chemical integrative samplers (POCIS) (see, Miege et al., J. Environ. Monit., 14:626-635, 2012; epub Dec. 22, 2011). Samples in the R series were collected on or around National Wildlife Refuges in the Northeast and the GL series on tributaries of the Great Lakes, both were collected as part of collaborative projects with the US Fish and Wildlife Services. All other samples were collected as part of the USGS Chesapeake Bay Priority Ecosystems Science projects. Grab water samples were processed at the USGS, Leetown Science Center as described below.

POCIS samples: The POCIS membranes were shipped to the USGS, Columbia Environmental Research Center for analyte recovery. The procedures used for preparing the POCIS samples for analysis were described earlier (Alvarez et al., Environ. Toxicol. Chem. 28:1084-1095, 2009). Briefly, chemicals of interest were recovered from the POCIS sorbent using 50 mL of 1:1:8 (V:V:V) methanol:toluene:dichloromethane followed by 20 mL of ethyl acetate. The extracts were reduced by rotary evaporation, filtered, and composited into 2-POCIS equivalent samples thereby concentrating the amount of chemical present in each sample to aid in the detection.

Grab Water samples: Grab water samples were collected in 500 ml pre-cleaned amber glass bottles (1-Chem, Rockwood, Tenn.). Water was acidified to pH 3 using 6N hydrochloric acid, held on ice, and stored at 4° C. Within one week of collection, the preserved water samples were filtered through a GF/F filter (0.7 μm) using a solvent rinsed all-glass apparatus. Filters were rinsed with 1 ml of methanol to liberate soluble compounds from the retained suspended solids. Filtered samples and blanks were subjected to solid phase extraction (SPE) using OASIS® HLB (200 mg) glass cartridges (Waters Corporation, Milford, Mass.), following an existing protocol (Ciparis et al., Sci. Total Environ. 414:268-276, 2012). In short, cartridges were sequentially pre-conditioned and 400 ml of filtered samples were loaded onto the cartridge at a flow rate of 5-6 ml/minute (continuous vacuum). Analytes were eluted from the cartridge with 100% methanol and concentrated by rotary evaporation.

For biological testing, samples prepared as above were reconstituted in DMSO and diluted in growth media to a final 1,000× concentration from the original water volume while maintaining DMSO at <0.2%. Samples were added to cells for 30 minutes at 100× concentration or as indicated in the text.

Cell Lines and Translocation Assay

The 3617 and 3108 cell lines are derivatives of 3134 mouse mammary adenocarcinoma cell line that express green fluorescent protein (GFP)-tagged GR (GFP-GR) and AR (GFP-AR), respectively from a chromosomal locus under control of the tetracycline-repressible promoter (Walker et al., Methods (Comp. to Meth. Enzym.) 19:386-393, 1999; Klokk et al., Mol. Cell. Biol. 27:1823-1843, 2007). Prior to imaging, cells were grown overnight on 22-mm² coverslips in DMEM medium containing 10% charcoal stripped serum (Hyclone, Logan, Utah) without tetracycline (to allow the expression of the GFP-GR or GFP-AR, respectively) at a density of 2×10⁵ per 6-well plate. For the automated experiments conducted in 96 or 384 well plates, cell density was 10,000 or 2,500 cells per well, respectively. Cells were treated with vehicle control, hormones (100 nM) or water samples for 30 min at 37° C. at a final concentration of 100× for water samples (unless otherwise specified). Additional negative controls contained samples that tested the activity of the POCIS membranes themselves.

Upon treatment, cells were fixed with 4% paraformaldehyde in PBS for 15 minutes and washed three times with PBS. Cells on the 22-mm² coverslips were mounted in VECTASHIELD® mounting media with DAPI (Vector Laboratories, Inc.) and examined on a Leica DMRA microscope with Leica 100×1.3-N.A. oil immersion objective. Images were acquired in green (GFP-GR and GFP-AR) and UV (DAPI) channel with SenSys (Photometrics) camera with KAF1400 chip configured to collect 0.067-μm-diameter pixels. For the automated experiments conducted in 96 or 384 well plates, cells were stained with DRAQ5 (BioStatus Limited) at a dilution of 1:5000 for 15 minutes and after three final washes with PBS were imaged either immediately on the Perkin Elmer Opera Image Screening System or kept in PBS at 4° C. for later imaging.

Automated Imaging and Analysis by Perkin Elmer Opera Image Screening System

A Perkin Elmer Opera Image Screening System was used for fully automated collection of fluorescence images of cells. This system employed a 40× water immersion objective lens, laser illuminated Nipkow disk, and cooled CCD cameras to digitally capture high resolution confocal fluorescence micrographs (300 nm pixel size with 2×2 camera pixel binning). An algorithm was customized using the Acapella image analysis software development kit (Perkin Elmer) to automatically segment both the nucleus and cytoplasm of each cell in the digital micrographs. The algorithm also measured the mean GFP-GR or GFP-AR intensity in both compartments, and translocation was calculated as a ratio of these intensities. Each value was further normalized to the value for the control (DMSO) sample.

Gene Transcription Analysis

For gene transcription studies, 3134 cells or LNCaP cells (expressing endogenous GR and AR, respectively) were plated in 24-well dishes 24 hours before each experiment in DMEM (3134 cells) or RPMI (LNCaP cells) media supplemented with charcoal stripped fetal bovine serum (Hyclone, Logan, Utah). Cells were treated with water samples, vehicle control (DMSO), or GR and AR specific hormones for 30 minutes. To reduce cell stress, these experiments were performed under conditions of stable CO₂ and temperature levels throughout the duration of an experiment (though this is not essential for the assay). Cells were lysed in 600 μl of RLT buffer (with f3-mercaptoethanol added) followed by syringe/needle shearing. Total RNA was extracted using the RNeasy Mini Kit (Qiagen), including a DNaseI digestion step (RNase free DNase Set, Qiagen). One microgram (μg) of RNA was reverse transcribed (iScript cDNA Synthesis Kit, BioRad) in 20 μl reaction volume and 0.5 μl was used per Q-PCR reaction using SyBr green and Bio-Rad IQ system (BioRad, Hercules, Calif.). Primer sequences were designed to amplify nascent RNA (amplicons that cross an exon/intron boundary). The primer sequences are shown below. PCR was performed as recommended by a manufacturer. Standard curves were created by 10-fold serial dilution of template. The expression data from three or more independent experiments were normalized to the expression of a control geneβ-Actin (3134 cells) and GAPDH (LNCaP cells), the mean values and SEM were calculated and displayed as a fold change in relation to the control (DMSO treated) sample.

Primer Sequences for Q-PCR Analysis

SEQ ID Sequence NO: Mouse cells (3134) Per1 For CTTCTGGCAATGGCAAGGACTC  9 Per1 Rev CAGCATCATGCCATCATACACACA 10 Tgm2 For TGTCACCAGGGATGAGAGACGG 11 Tgm2 Rev TCCAAATCACACCTCTCCAGGAG 12 Lcn2 For ACCTCTCATTTCTTGCAGTTCCG 12 Lcn2 Rev CAGGATGGAGGTGACATTGTAGCT 13 β-Actin For AGTGTGACGTTGACATCCGTA 15 β-Actin Rev GCCAGAGCAGTAATCTCCTTCT 16 Human cells (LNCaP) hNKX3.1 For TGACAGTGGGCTGTTTGTTC 17 hNKX3.1 Rev AAGACCCCAAGTGCCTTTCT 18 hRHOU For TTTCAAGGATGCTGGCTCTT 19 hRHOU Rev GGCCTCAGCTTGTCAAATTC 20 GAPDH For AAGGTGAAGGTCGGAGTCAAC 21 GAPDH Rev GGGGTCATTGATGGCAACAATA 22

Statistical Analyses

Data were analyzed using the statistical functions of IBM SPSS Statistics 19 and SigmaPlot 11 (SPSS Inc., Chicago, Ill.). From the repeated experiments, the mean value was calculated for each sample. The mean values were used in a one-way analysis of variance test. If a significant F-value of P<0.05 was obtained, a Dunnett's multiple comparison versus the control group analysis was conducted.

TABLE 2 Collection sites and collection time of the first sample set. Collection Samples Date/year Location method Blank Oct.-Nov. 2005 POCIS WV2 Oct.-Nov. 2005 South Branch Potomac, Franklin, WV POCIS WV3 Oct.-Nov. 2005 South Branch Potomac, Springfield, WV POCIS WV4 Oct.-Nov. 2005 South Branch Potomac, Moorefield, WV POCIS WV5 Oct.-Nov. 2005 Elk River, WV POCIS WV6 Oct.-Nov. 2005 South Branch Potomac, Petersburg Gap, WV POCIS WV7 Oct.-Nov. 2005 Greenbrier River, WV POCIS SS83 Jun. 1, 2007 POCIS SS92 May 3, 2007-Jun. 7, 2007 Gauley River, WV POCIS SS93 Apr. 11, 2007-May 9, 2007 Lower Conococheague River, MD POCIS SS94 Apr. 11, 2007-May 9, 2007 Upper Conococheague River, MD POCIS SS95 Apr. 27, 2007-May 31, 2007 South Branch Potomac, Petersburg Gap, WV POCIS SS97 Apr. 11, 2007-May 9, 2007 Lower Monocacy River, MD POCIS SS98 Apr. 5, 2007-May 9, 2007 South Fork, Shenandoah River, VA POCIS

TABLE 3 Synthetic glucocorticoids surveyed by monitoring the mass spectrometric data for the presence of the corresponding molecular ion in sample SS97 1 amcinonide 2 betamethasone 3 budesonide 4 clobetasone 5 clobetasol 6 propionate 7 desonide 8 fluocinonide 9 fluocinolone acetonide 10 fluocortolone 11 fluprednidene acetate 12 halcinonide 13 hydrocortisone 14 hydrocortisone-17-butyrate 15 methylprednisolone 16 mometasone 17 mometasone furoate 18 prednicarbate 19 prednisolone 20 prednisone 21 triamcinolone acetonide

TABLE 4 Closest EIMS library matches of the mass spectra of chromatographic peaks 1-3 in FIG. 1D. ~Ob- Peak served Closest EIMS # MW Library Match Structure 1 272 7α-Hydroxy-5α- androstan-3-one MW 290

2 286 Androst-4- en-3,6-dione MW 286

or 4,4-Dimethyl- androst-5-ene MW 286

3 272 ? eα-Hydroxy-17- ethylidene-5α- androstane MW 302

Table 5A-5B contains information about additional samples tested for GFP-GR and GFP-AR translocation efficiency.

TABLE 5A Geographic location, time and methods of collection of the water samples. Collection Samples Date/year Location method Plate 1 R1 Sept. 2, 2008 Ohio River, Wheeling WV Grab sample R2 Sept. 3, 2008 Ohio River, Parkersburg, WV Grab sample R3 Sept. 3, 2008 Upstream Brighton Dam, Tridelphia reservoir, MD Grab sample R4A Sept. 10, 2008 Patuxent/Western Branch, MD Grab sample R4E Sept. 10, 2008 Patuxent/Western Branch, MD (WWTP effluent) Grab sample R5 Sept. 15, 2008 Seneca River, NY Grab sample R6 Sept. 16, 2008 Seneca River, NY Grab sample R7 Sept. 22, 2008 St. Croix River, ME Grab sample R8 Sept. 23, 2008 St. Croix River, ME Grab sample R9 Oct. 2, 2008 Sudbury river, MA Grab sample R10 Oct. 3, 2008 Sudbury river, MA Grab sample R13 Oct. 15, 2008 Rappahanock River, VA Grab sample R14 Oct. 15, 2008 Rappahanock River, VA Grab sample R15 Oct. 6, 2008 Rappahanock River, VA Grab sample R16 Oct. 27, 2008 Darby Creek, PA Grab sample R16W Oct. 27, 2008 Darby Creek, PA (WWTP effluent) Grab sample R21 Sept. 1, 2009 Missisquoi River, VT Grab sample R22 Sept. 1, 2009 Missisquoi River, VT Grab sample R22W Sept. 1, 2009 Missisquoi River, VT (WWTP effluent) Grab sample R23 Sept. 14, 2009 Penobscot River, ME Grab sample R24 Sept. 15, 2009 Penobscot River, ME Grab sample R26 Sept. 22, 2009 Peconic Lake, NY Grab sample R27 Sept. 28, 2009 Potomac River, Pohick, VA Grab sample R27W Sept. 28, 2009 Potomac River, Pohick, VA (WWTP effluent) Grab sample R28 Sept. 29, 2009 Burke Lake, VA Grab sample R29 Oct. 5, 2009 Delaware River, Cherry Valley, DE Grab sample R30 Oct. 6, 2009 Delaware River, Easton, PA Grab sample R31 Oct. 13, 2009 Susquehanna River, Garret Island, PA Grab sample R32 Broad Oct. 14, 2009 Susquehanna River, Conowingo Dam, PA Grab sample R32 CON Oct. 14, 2009 Susquehanna River, Conowingo Dam, PA Grab sample PSS2a May 14, 2010 Gooney Run, VA Grab sample PSS2b Jun. 14, 2010 Gooney Run, VA Grab sample PSS3a May 14, 2010 Passage Creek, VA Grab sample PSS3b Jun. 15, 2010 Passage Creek, VA Grab sample PSS4a May 14, 2010 Stony Creek (upstream), VA Grab sample PSS4b Jun. 15, 2010 Stony Creek (upstream), VA Grab sample PSS5a May 14, 2010 Stony Creek (downstream), VA Grab sample PSS5b Jun. 15, 2010 Stony Creek (downstream), VA Grab sample PSS6a May 13, 2010 Mill Creek, VA Grab sample PSS6b Jun. 14, 2010 Mill Creek, VA Grab sample PSS7a May 14, 2010 Hawksbill Creek, VA Grab sample PSS7b Jun. 14, 2010 Hawksbill Creek, VA Grab sample PSS8a May 13, 2010 Smith Creek (downstream), VA Grab sample PSS8b Jun. 14, 2010 Smith Creek (downstream), VA Grab sample PSS9a May 12, 2010 Naked Creek, VA Grab sample PSS9b Jun. 15, 2010 Naked Creek, VA Grab sample PSS10a May 13, 2010 Briery Branch, VA Grab sample PSS10b Jun. 15, 2010 Briery Branch, VA Grab sample PSS11a May 13, 2010 Smith Creek (upstream), VA Grab sample PSS11b Jun. 14, 2010 Smith Creek (upstream), VA Grab sample PSS12a May 13, 2010 Long Glade Creek, VA Grab sample PSS12b Jun. 14, 2010 Long Glade Creek, VA Grab sample PSS13a May 13, 2010 Linville Creek, VA Grab sample PSS13b Jun. 14, 2010 Linville Creek, VA Grab sample PSS14a May 13, 2010 Long Meadow Run, VA Grab sample PSS14b Jun. 14, 2010 Long Meadow Run, VA Grab sample PSS15a May 13, 2010 Muddy Creek, VA Grab sample PSS15b Jun. 15, 2010 Muddy Creek, VA Grab sample PSS16a May 12, 2010 Cooks Creek, VA Grab sample PSS16b Jun. 14, 2010 Cooks Creek, VA Grab sample Dairy Sept. 28, 2010 North Fork Shenandoah at Woodstock, VA Grab sample LF1a Oct. 15, 2008 WWTP1 effluent, Rappahannock river, Little Falls, VA Grab sample LF2a Oct. 15, 2008 WWTP2 effluent, Rappahannock river, Little Falls, VA Grab sample LF3a Oct. 15, 2008 WWTP3 effluent, Rappahannock river, Little Falls, VA Grab sample LF4a Oct. 15, 2008 WWTP4 effluent, Rappahannock river, Little Falls, VA Grab sample SUS1 May 12, 2009 Susquehanna river at Mahantango Access, PA Grab sample SUS2 May 13, 2009 West Branch Susquehanna river, PA Grab sample Plate 2 SUS5 Apr. 21, 2010- Juniata River, Newport, PA POCIS Jun. 1, 2010 SUS6 Apr. 21, 2010- Susquehanna River at Mahantango Creek, PA POCIS Jun. 1, 2010 DE1 Apr. 19, 2010- Delaware River, Yardley, PA POCIS Jun. 3, 2010 AL1 Apr. 28, 2010- Allegheny River, Kittanning, PA POCIS Jun. 7, 2010 PSS16 May 12, 2010- Cooks Creek, VA POCIS Jun. 14, 2010 PSS09 May 12, 2010- Naked Creek, VA POCIS Jun. 15, 2010 PSS15 May 13, 2010- Muddy Creek, VA POCIS Jun. 15, 2010 PSS10 May 13, 2010- Briery Branch, VA POCIS Jun. 15, 2010 PSS12 May 13, 2010- Long Glade Creek, VA POCIS Jun. 14, 2010 PSS11 May 13, 2010- Smith Creek (upstream), VA POCIS Jun. 14, 2010 PSS13 May 13, 2010- Linville Creek, VA POCIS Jun. 14, 2010 PSS14 May 13, 2010- Long Meadow Run, VA POCIS Jun. 14, 2010 PSS08 May 13, 2010- Smith Creek (downstream), VA POCIS Jun. 14, 2010 PSS06 May 13, 2010- Mill Creek, VA POCIS Jun. 14, 2010 PSS02 May 14, 2010- Gooney Run, VA POCIS Jun. 14, 2010 PSS07 May 14, 2010- Hawksbill Creek, VA POCIS Jun. 14, 2010 PSS03 May 14, 2010- Passage Creek, VA POCIS Jun. 14, 2010 PSS05 May 14, 2010- Stony Creek (downstream), VA POCIS Jun. 14, 2010 PSS04 May 14, 2010- Stony Creek (upstream), VA POCIS Jun. 14, 2010 FAB Jun. 1, 2010 Blank POCIS 1FB Jun. 1, 2010 Blank POCIS 2FB Jun. 1, 2010 Blank POCIS 3FB Jun. 1, 2010 Blank POCIS 4FV Jun. 1, 2010 Blank POCIS 5FB Jun. 1, 2010 Blank POCIS 6FB Jun. 1, 2010 Blank POCIS 7FB Jun. 1, 2010 Blank POCIS 8FB Jun. 1, 2010 Blank POCIS 9FB Jun. 1, 2010 Blank POCIS 10FB Jun. 1, 2010 Blank POCIS 11FB Jun. 1, 2010 Blank POCIS 12FB Jun. 1, 2010 Blank POCIS 13FB Jun. 1, 2010 Blank POCIS 14FB Jun. 1, 2010 Blank POCIS 15FB Jun. 1, 2010 Blank POCIS 16FB Jun. 1, 2010 Blank POCIS 17FB Jun. 1, 2010 Blank POCIS 18FB Jun. 1, 2010 Blank POCIS 19FB Jun. 1, 2010 Blank POCIS BLANK Jun. 1, 2010 Blank POCIS R38 Sept. 20, 2010 PA Erie (Pond H) Grab sample R39 Sept. 28, 2010 NJ Great Swamp (Hidden Valley Nursery) Grab sample R40 Oct. 4, 2010 VA Back Bay Grab sample R41 Oct. 5, 2010 VA Wilna Pond Grab sample R42 Oct. 6, 2010 VA Chandler's Mill Pond Grab sample R43 Oct. 13, 2010 MD Patuxent (Snowden Pond) Grab sample R44 Oct. 13, 2010 MD Patuxent (Cash Lake) Grab sample GL1 Oct. 1, 2010 Genesee River, NY Grab sample GL2W Oct. 1, 2010 St. Louis River, Duluth, MN (WWTP effluent) Grab sample GL2P Oct. 1, 2010 St. Louis River, Duluth, MN (Power Plant effluent) Grab sample GL5 Oct. 1, 2010 Fox river, Green Bay, WI Grab sample GL4CSOa Oct. 1, 2010 Swan Creek, Ohio Grab sample GL4CSOb Oct. 1, 2010 Swan Creek, Ohio Grab sample GL4CSOc Oct. 1, 2010 Swan Creek, Ohio Grab sample GL3a Oct. 1, 2010 Detroit River, MI Grab sample GL3b Oct. 1, 2010 Detroit River, MI Grab sample GL3c Oct. 1, 2010 Detroit River, MI Grab sample R36 Sept. 14, 2010 Missisquoi River (Gander Bay & Goose Bay), VT Grab sample R37 Sept. 16, 2010 Lake Umbagog, MA Grab sample

TABLE 5B Activity of the samples in the GFP-GR and GFP-AR translocation assays (P < 0.01 and P < 0.05, asterisks). GR translocation AR translocation Samples P < 0.01 P < 0.05 P < 0.01 P < 0.05 Plate 1 R1 FALSE FALSE FALSE FALSE R2 FALSE FALSE FALSE FALSE R3 FALSE FALSE FALSE FALSE R4A * * * * R4E * * * * R5 FALSE FALSE FALSE FALSE R6 FALSE FALSE FALSE FALSE R7 FALSE FALSE FALSE FALSE R8 FALSE FALSE * * R9 FALSE FALSE * * R10 FALSE FALSE * * R13 FALSE FALSE FALSE FALSE R14 FALSE FALSE FALSE FALSE R15 FALSE FALSE * * R16 FALSE FALSE * * R16W * * FALSE * R21 FALSE FALSE FALSE FALSE R22 FALSE FALSE FALSE FALSE R22W FALSE FALSE FALSE FALSE R23 FALSE FALSE FALSE FALSE R24 FALSE FALSE FALSE FALSE R26 FALSE FALSE FALSE FALSE R27 * * FALSE FALSE R27W FALSE FALSE FALSE FALSE R28 FALSE FALSE FALSE FALSE R29 FALSE FALSE FALSE FALSE R30 FALSE FALSE FALSE FALSE R31 FALSE FALSE FALSE FALSE R32 Broad FALSE FALSE FALSE FALSE R32 CON FALSE FALSE FALSE FALSE PSS2a FALSE FALSE FALSE FALSE PSS2b FALSE FALSE FALSE FALSE PSS3a FALSE FALSE FALSE FALSE PSS3b FALSE FALSE FALSE FALSE PSS4a FALSE FALSE FALSE FALSE PSS4b FALSE FALSE FALSE FALSE PSS5a FALSE FALSE FALSE FALSE PSS5b FALSE FALSE FALSE FALSE PSS6a FALSE FALSE FALSE FALSE PSS6b FALSE FALSE * * PSS7a FALSE FALSE FALSE FALSE PSS7b FALSE FALSE FALSE FALSE PSS8a FALSE FALSE FALSE FALSE PSS8b FALSE FALSE FALSE FALSE PSS9a FALSE FALSE FALSE FALSE PSS9b FALSE FALSE FALSE FALSE PSS10a FALSE FALSE FALSE FALSE PSS10b FALSE FALSE FALSE FALSE PSS11a FALSE FALSE FALSE FALSE PSS11b FALSE FALSE FALSE * PSS12a FALSE FALSE FALSE FALSE PSS12b FALSE FALSE * * PSS13a FALSE FALSE FALSE FALSE PSS13b FALSE FALSE * * PSS14a FALSE FALSE FALSE FALSE PSS14b FALSE FALSE * * PSS15a FALSE FALSE * * PSS15b FALSE FALSE FALSE FALSE PSS16a FALSE FALSE FALSE FALSE PSS16b FALSE FALSE * * Dairy FALSE FALSE FALSE FALSE LF1a FALSE * * * LF2a * * * * LF3a * * FALSE FALSE LF4a * * FALSE * SUS1 FALSE FALSE FALSE FALSE SUS2 FALSE FALSE FALSE FALSE Plate2 SUS5 * * * * SUS6 * * * * DE1 * * * * AL1 * * * * PSS16 * * * * PSS09 * * * * PSS15 * * * * PSS10 * * * * PSS12 * * * * PSS11 * * FALSE * PSS13 * * * * PSS14 * * * * PSS08 * * FALSE * PSS06 * * * * PSS02 * * * * PSS07 * * * * PSS03 FALSE FALSE FALSE FALSE PSS05 * * * * PSS04 * * FALSE FALSE FAB FALSE FALSE FALSE FALSE 1FB FALSE FALSE FALSE FALSE 2FB FALSE FALSE FALSE FALSE 3FB FALSE FALSE FALSE FALSE 4FV FALSE FALSE FALSE FALSE 5FB FALSE FALSE FALSE FALSE 6FB FALSE FALSE FALSE FALSE 7FB FALSE FALSE FALSE FALSE 8FB FALSE FALSE FALSE FALSE 9FB FALSE FALSE FALSE FALSE 10FB FALSE FALSE FALSE FALSE 11FB FALSE FALSE FALSE FALSE 12FB FALSE FALSE FALSE FALSE 13FB FALSE FALSE FALSE FALSE 14FB FALSE FALSE FALSE FALSE 15FB FALSE FALSE FALSE FALSE 16FB FALSE FALSE FALSE FALSE 17FB FALSE FALSE FALSE FALSE 18FB FALSE FALSE FALSE FALSE 19FB FALSE FALSE FALSE FALSE BLANK FALSE FALSE FALSE FALSE R38 FALSE FALSE FALSE FALSE R39 FALSE FALSE FALSE FALSE R40 FALSE FALSE FALSE FALSE R41 FALSE FALSE FALSE FALSE R42 FALSE FALSE FALSE FALSE R43 FALSE FALSE FALSE FALSE R44 FALSE FALSE FALSE FALSE GL1 FALSE FALSE FALSE FALSE GL2W * * FALSE * GL2P FALSE FALSE FALSE FALSE GL5 FALSE FALSE FALSE FALSE GL4CSOa FALSE * * * GL4CSOb * * * * GL4CSOc FALSE FALSE * * GL3a FALSE FALSE FALSE FALSE GL3b FALSE FALSE FALSE FALSE GL3c * * FALSE FALSE R36 FALSE FALSE FALSE FALSE R37 FALSE FALSE FALSE FALSE

Results & Discussion

Accumulated data hint at an unacknowledged and potentially wide spread contamination with glucocorticoids (GCs) at biologically-relevant concentrations. To directly examine this possibility, 10 water samples collected from different locations (FIG. 2A and Table 2) were tested for GC activity using GFP-GR translocation assay. The presence of GC activity in one of these samples (SS97) was revealed by the accumulation of GFP-GR in the nucleus within 30 minutes (FIG. 1C, images). Furthermore, this sample induced transcriptional activity as measured by an increase of the nascent transcript of the GR-regulated gene, Per1, to a significantly higher level than the positive control, corticosterone (at a physiologically relevant dose of 100 nM) (FIG. 1C, graph).

In an attempt to determine the active constituent(s) in sample SS97, known corticosteroids (dexamethasone and corticosterone) were tested by high performance liquid chromatography/mass spectrometry (HPLC/MS) analysis to establish chromatographic retention times on a C18 HPLC column using published techniques (Chang et al., Environ. Sci. Technol. 43, 7691-7698, 2009). In addition, 20 other synthetic GCs were surveyed by monitoring the mass spectrometric data for the presence of the corresponding molecular ions (Table 3). Under these assay conditions, sample SS97 showed no evidence of any known compounds tested. Next, sample SS97 was subjected to HPLC fractionation followed by biological testing. Four of the eleven HPLC fractions showed activity in the nuclear translocation assay (FIG. 2C). Again, when these fractions were tested by ultra-performance liquid chromatography/mass spectrometry (UPLC/MS), no known GCs compounds were detected. The active fractions were also analyzed by gas chromatography/MS (GC/MS) (Mansilha et al., J. Chromatogr. A 1217(43):6681-6691, 2010), and appeared similar in composition to volatile components. The mass spectra extracted from the GC/MS analysis were searched in both the NIST/EPA/NIH Mass Spectral Library 1998 and in the Wiley Mass Spectra Database of Androgens, Estrogens, and other Steroids 2010 (AES 2010), yielding no hits of high certainty for any of the peaks.

Visual comparison of the mass spectra of chromatographic peaks 1-3 (FIG. 1D) with standard spectra from the AES 2010 database (FIG. 3) suggested similarities to known androstane-class compounds (FIG. 1D, Table 4). One of these compounds, androst-4-en-3,6-dione (peak 2), was synthesized (Hunter & Priest, Steroids 71, 30, 2006) and further tested for biological activity. Androst-4-en-3,6-dione did not induce GFP-GR translocation (data not shown) whereas it induced GFP-tagged androgen receptor (GFP-AR) translocation (FIG. 1E) using a GFP-AR expressing cell line, 3108 (Klokk et al., Mol. Cell. Biol. 27:1823-1843, 2007). These data suggest that, in addition to GCs, sample SS97 also contains androgenic activity.

Androgens are the original anabolic steroids and the precursor of all estrogens, the female sex hormones. Through their binding to androgen receptor (AR), they control the development and maintenance of male characteristics in vertebrates (Gottlieb et al., Reprod. Biomed. Online. 10:42-48, 2005). Similarly to the GR, AR is largely cytoplasmic in the absence of its ligand, and rapidly translocates to the nucleus in response to testosterone (Klokk et al., Mol. Cell. Biol. 27:1823-1843, 2007) (FIG. 1E).

We conclude that environmental degradation and metabolic processes alter the structure of the glucocorticoid(s) in water samples, producing bioactive chemical structures which are not contained in the existing databases. Rapid transformation of hormonal steroids by aquatic microorganisms has been reported previously (Yin et al., Environ. Int. 28:545-551, 2002). We also conclude that, in contrast to the traditional chemical analysis, the translocation assay described herein is faster, cheaper, and also detects biologically relevant hormonal activity which cannot readily be discerned by chemical methods. Translocation assay allows unbiased “non-candidate” approach for detection of EDCs and could be used in a powerful combination with fractionation methods and “forensic chemistry” in the discovery of novel bioactive ligands.

Next, the search was expanded to screen over 100 additional samples from water sources throughout 14 states in the US (Table 5A) for both, glucocorticoid and androgen activities. To accomplish this screening, the GFP-GR- and GFP-AR-expressing cell lines (Walker et al., Methods (Comp. to Meth. Enzym.) 19:386-393, 1999; Klokk et al., Mol. Cell. Biol. 27:1823-1843, 2007) were implemented in an automated imaging analysis system (Perkin Elmer Opera Image Screening System) and an algorithm for cytoplasm and nuclear segmentation was used to calculate translocation efficiency (FIGS. 4A and 4B). To test the sensitivity and reproducibility of the automated assay, translocation efficiency in response to known concentrations of the respective hormones was measured. GFP-GR translocated to the nucleus in a concentration-dependent manner in response to the rodent, human, as well as synthetic hormones (corticosterone, hydrocortisone, and dexamethasone, respectively) (FIG. 5A). The GFP-tagged AR also translocated to the nucleus in concentration-dependent manner in response to testosterone as well as synthesized androst-4-en-3,6-dione (FIGS. 5B and 5C). Confident in the sensitivity of the translocation assay, the additional water samples were tested after being divided into two plates: plate one [P1, (FIGS. 4D, 4E)] and plate two [P2, (FIGS. 6 and 6)]. Glucocorticoid activity was evident in over 28% (FIG. 4D and FIG. 6) and androgen activity in 37% (FIG. 4E and FIG. 7) of the 105 samples subjected to the high throughput screening (Tables 5A and 5B). When combined with the results obtained from the first manual screen of 10 samples (Table 2), glucocorticoid and androgen activity remained in the same range (27% and 35%, respectively). These results unambiguously demonstrate a wide spread contamination of the US water sources from 14 different states with both, glucocorticoid and androgenic activities (FIG. 3, Tables 5A and 5B).

Considering that the tested samples were collected over a span of several years (Tables 2 and 5A), we sought to determine whether the observed contaminations persist over time. Two of the previously identified contaminated sites (SS97 and GL2W) were revisited and new grab water samples were collected. As shown in FIGS. 4A and B (as well as in FIGS. S6, S7, S8, S9) both newly collected samples induced GFP-GR and GFP-AR nuclear translocation in a concentration-dependent manner, suggesting high and persisting water contamination at these sites. Tenfold concentrated samples from both locations were active in GR and AR translocation assays, and induced transcriptional activity. Moreover, at 1× concentration, sample SS97 induced significant GFP-GR translocation (FIG. 9A-insert) and activation of gene transcription from GR-responsive genes (FIG. 9E). These results indicate that the water at the SS97 location has biologically relevant glucocorticoid activity that is persistent over time.

Interestingly, 100× concentration of samples SS97 (FIG. 9F) and GL2W (FIG. 13C) were less potent than the lower doses in inducing gene transcription from AR-regulated genes. This could be an example of the well-known phenomenon of non-monotonic dose-response where the effects of the low doses of EDCs cannot be predicted by the effects observed at high doses (Vandenberg et al., Endocr. Rev., e-published ahead of printing on Mar. 14, 2012 as doi:10.1210/er.2011-1050). These results underscore the importance of examining the effects of a range of concentrations when using gene transcription analyses as a readout for the biological effect of EDCs. However, presence of inhibitory components or anti-estrogens cannot be ruled out and may warrant further investigation. In contrast, the GFP-GR and GFP-AR translocation assays were applicable to a wider range of concentrations including 100× doses. Thus, the translocation assay described herein is largely devoid of the non-monotonic dose-response effects observed by other detection methods, which makes it suitable for high-throughput screening.

SUMMARY

In conclusion, mammalian cell lines expressing GFP-tagged nuclear receptor constructs were utilized in an automated, highly reproducible, and low cost assay for detection of biologically active glucocorticoids and androgens in water sources. Using this high-throughput screening, combined with studies on transcriptional activation, glucocorticoid and androgen activities were discovered in water sources from 8 of 14 states in the US. This level of wide-spread contamination with steroids of both classes is a possible health hazard not only for the aquatic ecosystems, but may also negatively impact the human population. Largely unrestricted human activity with respect to many potential endocrine disruptors is of concern, and represents one of the main reasons for these wide-spread contaminations. Considering the largely unrestricted human activity in respect to many potential endocrine disruptors and limited methods (Roy & Pereira, Indian J. Exp. Biol 43:975-992, 2005) for their detection in the environment, there is an urgent need of better assays for EDC screening. The results discussed here not only highlight the prevalence of contamination of water sources with glucocorticoid and androgen activities, but also introduce a novel approach for monitoring the quality of water. This approach can be readily extended to other nuclear receptors and applied to detection of various classes of EDCs in the environment.

In view of the many possible embodiments to which the principles of the disclosed invention may be applied, it should be recognized that the illustrated embodiments are only preferred examples of the invention and should not be taken as limiting the scope of the invention. Rather, the scope of the invention is defined by the following claims. We therefore claim as our invention all that comes within the scope and spirit of these claims. 

We claim:
 1. A system for detecting or quantifying a ligand of a superfamily receptor protein in an environmental sample, the system comprising: a first mammalian cell expressing a first traceable fusion protein; a second mammalian cell expressing a second traceable fusion protein; and a detection system for the detection of the cytoplasm-to-nuclear translocation of the marker proteins, wherein the first and second traceable fusion proteins independently comprise either: (1) a superfamily receptor protein, and a marker protein domain; or (2) the cytoplasmic/nuclear translocation domain of glucocorticoid receptor, the ligand binding domain of a superfamily receptor protein, and a marker protein domain.
 2. The system of claim 1, wherein the ligand is an agonist or an antagonist.
 3. The system of claim 1, wherein the first traceable fusion protein binds a different ligand than the second traceable fusion protein.
 4. The system of claim 3, wherein the marker protein domain is different in the first and second traceable fusion proteins.
 5. The system of claim 1, wherein the marker protein domain is a fluorescent protein domain.
 6. The system of claim of claim 1, wherein the ligand for the first or second traceable fusion protein is a natural ligand for the superfamily receptor protein of the traceable fusion protein, or a natural or synthetic compound that binds competitively therewith.
 7. The system of claim 1, additionally comprising: one or more compounds and/or compositions that stably associate with a traceable fusion protein of the system in the absence of a ligand for the ligand binding domain of the traceable fusion protein, and which dissociates from the fusion protein in the presence of a ligand for the ligand binding domain of the traceable fusion protein.
 8. The system of claim 1, wherein the mammalian cells are human cells.
 9. The system of claim 1, comprising at least four mammalian cell lines each expressing a different traceable fusion protein, wherein at least one traceable fusion protein binds a glucocorticoid, at least one traceable fusion protein binds an androgen, at least one traceable fusion protein binds a progestin, and at least one traceable fusion protein binds an aryl hydrocarbon.
 10. The system of claim 1, provided as a kit.
 11. The system of claim 1, wherein the environmental sample comprises a water sample, soil sample, or air sample.
 12. The system of claim 11, wherein the sample comprises a water sample comprising surface water, sub-surface (ground) water, rain, run-off, well water, spring water, drinking water (processed or not), river water, estuary water, ocean water, effluent, treated sewage or untreated sewage.
 13. A method for detecting or quantifying an endocrine disruptor chemical (EDC) ligand in an environmental sample, the method comprising: contacting with the environmental sample a human cell expressing in its cytoplasm a fusion protein comprising: a receptor for the ligand, which receptor translocates from the cytoplasm to the nucleus upon ligand binding; and a marker protein domain; and detecting cytoplasmic to nuclear translocation of the fusion protein in response to a ligand of the ligand binding domain in the water sample.
 14. The method of any claim 13, wherein the environmental sample comprises a water sample, soil sample, or air sample.
 15. The method of claim 14, wherein the sample comprises a water sample comprising surface water, sub-surface (ground) water, rain, run-off, well water, spring water, drinking water (processed or not), river water, estuary water, ocean water, effluent, treated sewage or untreated sewage.
 16. A method of determining the concentration of an endocrine disruptor chemical (EDC) ligand in an environmental sample, the method comprising: contacting with the environmental sample a population of eukaryotic cells expressing in their cytoplasm a fusion protein comprising: a receptor for the ligand, which receptor translocates from the cytoplasm to the nucleus upon ligand binding; and a marker protein domain; and scanning one or more test cell(s) to obtain signal data from the marker of the fusion protein; converting the signal data to obtain the cellular location of the labeled protein in the test cell(s); and analyzing the signal data using an analysis system having an algorithm to calculate changes in distribution of the labeled fusion protein between the cytoplasm and the nucleus of the test cell(s), the analysis system having the capability of providing an accurate reading of the concentration of the ligand.
 17. The method of claim 16, wherein the environmental sample comprises a water sample, soil sample, or air sample.
 18. The method of claim 17, wherein the sample comprises a water sample comprising surface water, sub-surface (ground) water, rain, run-off, well water, spring water, drinking water (processed or not), river water, estuary water, ocean water, effluent, treated sewage or untreated sewage. 